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Adaptive filter theory / / Simon Haykin ; international edition contributions by Telagarapu Prabhakar
Adaptive filter theory / / Simon Haykin ; international edition contributions by Telagarapu Prabhakar
Autore Haykin Simon S. <1931->
Edizione [Fifth edition, International edition.]
Pubbl/distr/stampa Upper Saddle River : , : Pearson, , [2014]
Descrizione fisica 1 online resource (912 pages) : illustrations (some color)
Disciplina 621.3815324
Collana Always learning
Soggetto topico Adaptive filters
ISBN 0-273-77572-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title -- Contents -- Preface -- Acknowledgments -- Background and Preview -- 1. The Filtering Problem -- 2. Linear Optimum Filters -- 3. Adaptive Filters -- 4. Linear Filter Structures -- 5. Approaches to the Development of Linear Adaptive Filters -- 6. Adaptive Beamforming -- 7. Four Classes of Applications -- 8. Historical Notes -- Chapter 1 Stochastic Processes and Models -- 1.1 Partial Characterization of a Discrete-Time Stochastic Process -- 1.2 Mean Ergodic Theorem -- 1.3 Correlation Matrix -- 1.4 Correlation Matrix of Sine Wave Plus Noise -- 1.5 Stochastic Models -- 1.6 Wold Decomposition -- 1.7 Asymptotic Stationarity of an Autoregressive Process -- 1.8 Yule-Walker Equations -- 1.9 Computer Experiment: Autoregressive Process of Order Two -- 1.10 Selecting the Model Order -- 1.11 Complex Gaussian Proceses -- 1.12 Power Spectral Density -- 1.13 Propert ies of Power Spectral Density -- 1.14 Transmission of a Stationary Process Through a Linear Filter -- 1.15 Cramér Spectral Representation for a Stationary Process -- 1.16 Power Spectrum Estimation -- 1.17 Other Statistical Characteristics of a Stochastic Process -- 1.18 Polyspectra -- 1.19 Spectral-Correlation Density -- 1.20 Summary and Discussion -- Problems -- Chapter 2 Wiener Filters -- 2.1 Linear Optimum Filtering: Statement of the Problem -- 2.2 Principle of Orthogonality -- 2.3 Minimum Mean-Square Error -- 2.4 Wiener-Hopf Equations -- 2.5 Error-Performance Surface -- 2.6 Multiple Linear Regression Model -- 2.7 Example -- 2.8 Linearly Constrained Minimum-Variance Filter -- 2.9 Generalized Sidelobe Cancellers -- 2.10 Summary and Discussion -- Problems -- Chapter 3 Linear Prediction -- 3.1 Forward Linear Prediction -- 3.2 Backward Linear Prediction -- 3.3 Levinson-Durbin Algorithm -- 3.4 Properties of Prediction-Error Filters -- 3.5 Schur-Cohn Test.
3.6 Autoregressive Modeling of a Stationary Stochastic Process -- 3.7 Cholesky Factorization -- 3.8 Lattice Predictors -- 3.9 All-Pole, All-Pass Lattice Filter -- 3.10 Joint-Process Estimation -- 3.11 Predictive Modeling of Speech -- 3.12 Summary and Discussion -- Problems -- Chapter 4 Method of Steepest Descent -- 4.1 Basic Idea of the Steepest-Descent Algorithm -- 4.2 The Steepest-Descent Algorithm Applied to the Wiener Filter -- 4.3 Stability of the Steepest-Descent Algorithm -- 4.4 Example -- 4.5 The Steepest-Descent Algorithm Viewed as a Deterministic Search Method -- 4.6 Virtue and Limitation of the Steepest-Descent Algorithm -- 4.7 Summary and Discussion -- Problems -- Chapter 5 Method of Stochastic Gradient Descent -- 5.1 Principles of Stochastic Gradient Descent -- 5.2 Application 1: Least-Mean-Square (LMS) Algorithm -- 5.3 Application 2: Gradient-Adaptive Lattice Filtering Algorithm -- 5.4 Other Applications of Stochastic Gradient Descent -- 5.5 Summary and Discussion -- Problems -- Chapter 6 The Least-Mean-Square (LMS) Algorithm -- 6.1 Signal-Flow Graph -- 6.2 Optimality Considerations -- 6.3 Applications -- 6.4 Statistical Learning Theory -- 6.5 Transient Behavior and Convergence Considerations -- 6.6 Efficiency -- 6.7 Computer Experiment on Adaptive Prediction -- 6.8 Computer Experiment on Adaptive Equalization -- 6.9 Computer Experiment on a Minimum-Variance Distortionless-Response Beamformer -- 6.10 Summary and Discussion -- Problems -- Chapter 7 Normalized Least-Mean-Square (LMS) Algorithm and Its Generalization -- 7.1 Normalized LMS Algorithm: The Solution to a Constrained Optimization Problem -- 7.2 Stability of the Normalized LMS Algorithm -- 7.3 Step-Size Control for Acoustic Echo Cancellation -- 7.4 Geometric Considerations Pertaining to the Convergence Process for Real-Valued Data -- 7.5 Affine Projection Adaptive Filters.
7.6 Summary and Discussion -- Problems -- Chapter 8 Block-Adaptive Filters -- 8.1 Block-Adaptive Filters: Basic Ideas -- 8.2 Fast Block LMS Algorithm -- 8.3 Unconstrained Frequency-Domain Adaptive Filters -- 8.4 Self-Orthogonalizing Adaptive Filters -- 8.5 Computer Experiment on Adaptive Equalization -- 8.6 Subband Adaptive Filters -- 8.7 Summary and Discussion -- Problems -- Chapter 9 Method of Least-Squares -- 9.1 Statement of the Linear Least-Squares Estimation Problem -- 9.2 Data Windowing -- 9.3 Principle of Orthogonality Revisited -- 9.4 Minimum Sum of Error Squares -- 9.5 Normal Equations and Linear Least-Squares Filters -- 9.6 Time-Average Correlation Matrix Φ -- 9.7 Reformulation of the Normal Equations in Terms of Data Matrices -- 9.8 Properties of Least-Squares Estimates -- 9.9 Minimum-Variance Distortionless Response (MVDR) Spectrum Estimation -- 9.10 Regularized MVDR Beamforming -- 9.11 Singular-Value Decomposition -- 9.12 Pseudoinverse -- 9.13 Interpretation of Singular Values and Singular Vectors -- 9.14 Minimum-Norm Solution to the Linear Least-Squares Problem -- 9.15 Normalized LMS Algorithm Viewed as the Minimum-Norm Solution to an Underdetermined Least-Squares Estimation Problem -- 9.16 Summary and Discussion -- Problems -- Chapter 10 The Recursive Least-Squares (RLS) Algorithm -- 10.1 Some Preliminaries -- 10.2 The Matrix Inversion Lemma -- 10.3 The Exponentially Weighted RLS Algorithm -- 10.4 Selection of the Regularization Parameter -- 10.5 Updated Recursion for the Sum of Weighted Error Squares -- 10.6 Example: Single-Weight Adaptive Noise Canceller -- 10.7 Statistical Learning Theory -- 10.8 Efficiency -- 10.9 Computer Experiment on Adaptive Equalization -- 10.10 Summary and Discussion -- Problems -- Chapter 11 Robustness -- 11.1 Robustness, Adaptation, and Disturbances.
11.2 Robustness: Preliminary Considerations Rooted in H∞ Optimization -- 11.3 Robustness of the LMS Algorithm -- 11.4 Robustness of the RLS Algorithm -- 11.5 Comparative Evaluations of the LMS and RLS Algorithms from the Perspective of Robustness -- 11.6 Risk-Sensitive Optimality -- 11.7 Trade-Offs Between Robustness and Efficiency -- 11.8 Summary and Discussion -- Problems -- Chapter 12 Finite-Precision Effects -- 12.1 Quantization Errors -- 12.2 Least-Mean-Square (LMS) Algorithm -- 12.3 Recursive Least-Squares (RLS) Algorithm -- 12.4 Summary and Discussion -- Problems -- Chapter 13 Adaptation in Nonstationary Environments -- 13.1 Causes and Consequences of Nonstationarity -- 13.2 The System Identification Problem -- 13.3 Degree of Nonstationarity -- 13.4 Criteria for Tracking Assessment -- 13.5 Tracking Performance of the LMS Algorithm -- 13.6 Tracking Performance of the RLS Algorithm -- 13.7 Comparison of the Tracking Performance of LMS and RLS Algorithms -- 13.8 Tuning of Adaptation Parameters -- 13.9 Incremental Delta-Bar-Delta (IDBD) Algorithm -- 13.10 Autostep Method -- 13.11 Computer Experiment: Mixture of Stationary and Nonstationary Environmental Data -- 13.12 Summary and Discussion -- Problems -- Chapter 14 Kalman Filters -- 14.1 Recursive Minimum Mean-Square Estimation for Scalar Random Variables -- 14.2 Statement of the Kalman Filtering Problem -- 14.3 The Innovations Process -- 14.4 Estimation of the State Using the Innovations Process -- 14.5 Filtering -- 14.6 Initial Conditions -- 14.7 Summary of the Kalman Filter -- 14.8 Optimality Criteria for Kalman Filtering -- 14.9 Kalman Filter as the Unifying Basis for RLS Algorithms -- 14.10 Covariance Filtering Algorithm -- 14.11 Information Filtering Algorithm -- 14.12 Summary and Discussion -- Problems -- Chapter 15 Square-Root Adaptive Filtering Algorithms.
15.1 Square-Root Kalman Filters -- 15.2 Building Square-Root Adaptive Filters on the Two Kalman Filter Variants -- 15.3 QRD-RLS Algorithm -- 15.4 Adaptive Beamforming -- 15.5 Inverse QRD-RLS Algorithm -- 15.6 Finite-Precision Effects -- 15.7 Summary and Discussion -- Problems -- Chapter 16 Order-Recursive Adaptive Filtering Algorithm -- 16.1 Order-Recursive Adaptive Filters Using Least-Squares Estimation: An Overview -- 16.2 Adaptive Forward Linear Prediction -- 16.3 Adaptive Backward Linear Prediction -- 16.4 Conversion Factor -- 16.5 Least-Squares Lattice (LSL) Predictor -- 16.6 Angle-Normalized Estimation Errors -- 16.7 First-Order State-Space Models for Lattice Filtering -- 16.8 QR-Decomposition-Based Least-Squares Lattice (QRD-LSL) Filters -- 16.9 Fundamental Properties of the QRD-LSL Filter -- 16.10 Computer Experiment on Adaptive Equalization -- 16.11 Recursive (LSL) Filters Using A Posteriori Estimation Errors -- 16.12 Recursive LSL Filters Using A Priori Estimation Errors with Error Feedback -- 16.13 Relation Between Recursive LSL and RLS Algorithms -- 16.14 Finite-Precision Effects -- 16.15 Summary and Discussion -- Problems -- Chapter 17 Blind Deconvolution -- 17.1 Overview of Blind Deconvolution -- 17.2 Channel Identifiability Using Cyclostationary Statistics -- 17.3 Subspace Decomposition for Fractionally Spaced Blind Identification -- 17.4 Bussgang Algorithm for Blind Equalization -- 17.5 Extension of the Bussgang Algorithm to Complex Baseband Channels -- 17.6 Special Cases of the Bussgang Algorithm -- 17.7 Fractionally Spaced Bussgang Equalizers -- 17.8 Estimation of Unknown Probability Distribution Function of Signal Source -- 17.9 Summary and Discussion -- Problems -- Epilogue -- 1. Robustness, Efficiency, and Complexity -- 2. Kernel-Based Nonlinear Adaptive Filtering -- Appendix A Theory of Complex Variables.
A.1 Cauchy-Riemann Equations.
Record Nr. UNINA-9910150209303321
Haykin Simon S. <1931->  
Upper Saddle River : , : Pearson, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Cognitive dynamic systems : perception--action cycle, radar, and radio / / Simon Haykin [[electronic resource]]
Cognitive dynamic systems : perception--action cycle, radar, and radio / / Simon Haykin [[electronic resource]]
Autore Haykin Simon S. <1931->
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2012
Descrizione fisica 1 online resource (xii, 309 pages) : digital, PDF file(s)
Disciplina 003/.7
Soggetto topico Self-organizing systems
Cognitive radio networks
ISBN 1-107-21273-1
1-280-87888-6
1-139-12259-2
9786613720191
1-139-11468-9
0-511-81836-X
1-139-11249-X
1-139-12751-9
1-139-11685-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Introduction -- 2. The perception-action cycle -- 3. Power-spectrum estimation for sensing the environment -- 4. Bayesian filtering for state estimation of the environment -- 5. Dynamic programming for action in the environment -- 6. Cognitive radar -- 7. Cognitive radio -- 8. Epilogue.
Record Nr. UNINA-9910462648103321
Haykin Simon S. <1931->  
Cambridge : , : Cambridge University Press, , 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Cognitive dynamic systems : perception--action cycle, radar, and radio / / Simon Haykin [[electronic resource]]
Cognitive dynamic systems : perception--action cycle, radar, and radio / / Simon Haykin [[electronic resource]]
Autore Haykin Simon S. <1931->
Pubbl/distr/stampa Cambridge : , : Cambridge University Press, , 2012
Descrizione fisica 1 online resource (xii, 309 pages) : digital, PDF file(s)
Disciplina 003/.7
Soggetto topico Self-organizing systems
Cognitive radio networks
ISBN 1-107-21273-1
1-280-87888-6
1-139-12259-2
9786613720191
1-139-11468-9
0-511-81836-X
1-139-11249-X
1-139-12751-9
1-139-11685-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Introduction -- 2. The perception-action cycle -- 3. Power-spectrum estimation for sensing the environment -- 4. Bayesian filtering for state estimation of the environment -- 5. Dynamic programming for action in the environment -- 6. Cognitive radar -- 7. Cognitive radio -- 8. Epilogue.
Record Nr. UNINA-9910790302503321
Haykin Simon S. <1931->  
Cambridge : , : Cambridge University Press, , 2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Handbook on array processing and sensor networks / / [edited by] Simon Haykin, K.J. Ray Liu
Handbook on array processing and sensor networks / / [edited by] Simon Haykin, K.J. Ray Liu
Autore Haykin Simon S. <1931->
Edizione [1st edition]
Pubbl/distr/stampa [Piscataway, New Jersey] : , : IEEE, , c2009
Descrizione fisica 1 online resource (924 p.)
Disciplina 621.382/4
621.3822
621.3824
Altri autori (Persone) LiuK. J. Ray
HaykinSimon S
Collana Adaptive and learning systems for signal processing, communications and control series
Soggetto topico Sensor networks
Antenna arrays
Array processors
ISBN 1-282-54932-4
9786612549328
1-61344-501-6
0-470-48706-2
0-470-48705-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface (Simon Haykin and K. J. Ray Liu) -- Contributors -- Introduction (Simon Haykin) -- PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING -- 1. Wavefields. (Alfred Hanssen) -- 1.1 Introduction -- 1.2 Harmonizable Stochastic Processes -- 1.3 Stochastic Wavefields -- 1.4 Wave Dispersion -- 1.5 Conclusions -- 1.6 Acknowledgements -- References. -- 2. Spatial Spectrum Estimation (Petar M. Djuri) -- 2.1 Introduction -- 2.2 Fundamentals -- 2.3 Temporal Spectrum Estimation -- 2.4 Spatial Spectrum Estimation -- 2.5 Final Remarks -- References. -- 3. MIMO Radio Propagation (Tricia J. Willink) -- 3.1 Introduction -- 3.2 Space-Time Propagation Environment -- 3.3 Propagation Models -- 3.4 Measured Channel Characteristics -- 3.5 Stationarity -- 3.6 Summary -- References. -- 4. Robustness Issues in Sensor Array Processing (Alex B. Gershman) -- 4.1 Introduction -- 4.2 Direction-of-Arrival Estimation -- 4.3 Adaptive Beamforming -- 4.4 Conclusions -- Acknowledgments -- References. -- 5. Wireless Communication and Sensing in Multipath Environments Using Multiantenna Transceivers (Akbar M. Sayeed and Thiagarajan Sivanadyan) -- 5.1 Introduction and Overview -- 5.2 Multipath Wireless Channel Modeling in Time, Frequency and Space -- 5.3 Point-to-Point MIMO Wireless Communication Systems -- 5.4 Active Wireless Sensing with Wideband MIMO Transceivers -- 5.5 Concluding Remarks -- References -- PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF ARRAY SIGNAL PROCESSING. -- 6. Implicit Training and Array Processing for Digital Communication Systems (Aldo G. Orozco-Lugo, Mauricio Lara, and Desmond C. McLernon) -- 6.1 Introduction -- 6.2 Classification of Implicit Training Methods -- 6.3 IT-Based Estimation for a Single User -- 6.4 IT-Based Estimation for Multiple Users Exploiting Array Processing: Continuous Transmission -- 6.5 IT-Based Estimation for Multiple Users Exploiting Array Processing: Packet Transmission -- 6.6 Open Research Problems -- Acknowledgments -- References -- 7. Unitary Design of Radar Waveform Diversity Sets (Michael D. Zoltowski, Tariq R. Qureshi, Robert Calderbank, and Bill Moran).
7.1 Introduction -- 7.2 2 x 2 Space-Time Diversity Waveform Design -- 7.3 4 x 4 Space-Time Diversity Waveform Design -- 7.4 Waveform Families Based on Kronecker Products -- 7.5 Introduction to Data-Dependent Waveform Design -- 7.6 3 x 3 and 6 x 6 Waveform Scheduling -- 7.7 Summary -- References. -- 8. Acoustic Array Processing for Speech Enhancement (Markus Buck, Eberhard H Ansler, Mohamed Krini, Gerhard Schmidt and Tobias Wolff) -- 8.1 Introduction -- 8.2 Signal Processing in the Subband Domain -- 8.3 Multichannel Echo Cancelation -- 8.4 Speaker Localization -- 8.5 Beamforming -- 8.6 Sensor Calibration -- 8.7 Postprocessing -- 8.8 Conclusions -- References -- 9. Acoustic Beamforming for Hearing Aid Applications (Simon Doclo, Sharon Gannot, Marc Moonen and Ann Spriet) -- 9.1. Introduction -- 9.2. Overview of noise reduction techniques -- 9.3. Monaural beamforming -- 9.4. Binaural beamforming -- 9.5. Conclusion -- 10. Undetermined Blind Source Separation Using Acoustic Arrays (Shoji Makino, Shoko Araki, Stefan Winter and Hiroshi Sawada) -- 10.1 Introduction -- 10.2 Underdetermined Blind Source Separation of Speeches in Reverberant Environments -- 10.3 Sparseness of Speech Sources -- 10.4 Binary Mask Approach to Underdetermined BSS -- 10.5 MAP-Based Two-Stage Approach to Underdetermined BSS -- 10.6 Experimental Comparison with Binary Mask Approach and MAP-Based Two-Stage Approach -- 10.7 Concluding Remarks -- References -- 11. Array Processing in Astronomy (Douglas C.-J. Bock) -- 11.1 Introduction -- 11.2 Correlation Arrays -- 11.3 Aperture Plane Phased Arrays -- 11.4 Future Directions -- 11.5 Conclusion -- References. -- 12. Digital 3D/4D Ultrasound Imaging Array (Stergios Stergiopoulos) -- 12.1 Background -- 12.2 Next Generation 3D/4D Ultrasound Imaging Technology -- 12.3 Computing Architecture and Implementation Issues -- 12.4 An Experimental Planar Array Ultrasound Imaging System -- 12.5 Conclusion -- References -- PART III: FUNDAMENTAL ISSUES IN DISTRIBUTED SENSOR NETWORKS.
13. Self-Localization of Sensor Networks (Josh N. Ash and Randolph L. Moses) -- 13.1 Introduction -- 13.2 Measurement Types and Performance Bounds -- 13.3 Localization Algorithms -- 13.4 Relative and Transformation Error Decomposition -- 13.5 Conclusions -- References. -- 14. Multitarget Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo (Tom Vercauteren and Xiaodong Wang) -- 14.1 Introduction -- 14.2 System Description and Problem Formulation -- 14.3 Sequential Monte Carlo Methods -- 14.4 Joint Single-Target Tracking and Classification -- 14.5 Multiple-Target Tracking and Classification -- 14.6 Sensor Selection -- 14.7 Simulation Results -- Conclusion -- Appendix: Derviations of (14.38 and (14.40) -- References -- 15. Energy-Efficient Decentralized Estimation (Jin-Jun Xiao, Shuguang Cui and Zhi-Quan Luo) -- 15.5 Introduction -- 15.2 System Model -- 15.3 Digital Approaches -- 15.4 Analog Approaches -- 15.5 Analog versus Digital -- 15.6 Extension to Vector Model -- 15.7 Concluding Remarks -- Acknowledgments -- References. -- 16. Sensor Data Fusion with Application to Multitarget Tracking (R. Tharmarasa, K. Punithakumar, T. Kirubarajan and Y. Bar-Shalom) -- 16.1 Introduction -- 16.2 Tracking Filters -- 16.3 Data Association -- 16.4 Out-of-Sequence Measurements -- 16.5 Results with Real Data -- 16.6 Summary -- References. -- 17. Distributed Algorithms in Sensor Networks (Usman A. Khan, Soummya Kar and Jos A A Moura) -- 17.1 Introduction -- 17.2 Preliminaries -- 17.3 Distributed Detection -- 17.4 Consensus Algorithms -- 17.5 Zero-Dimension (Average) Consensus -- 17.6 Consensus in Higher Dimensions -- 17.7 Leader-Follower (Type) Algorithms -- 17.8 Localization in Sensor Networks -- 17.9 Linear System of Equations: Distributed Algorithm -- 17.10 Conclusions -- References. -- 18. Cooperative Sensor Communications (Ahmed K. Sadek, Weifeng Su and K. J. Ray Liu) -- 18.1 Introduction -- 18.2 Cooperative Relay Protocols -- 18.3 SER Analysis and Optimal Power Allocation.
18.4 Energy Efficiency in Cooperative Sensor Networks -- 18.5 Experimental Results -- 18.6 Conclusions -- References. -- 19. Distributed Source Coding (Zixiang Xiong, Angelos D. Liveris and Yang Yang) -- 19.1 Introduction -- 19.2 Theoretical Background -- 19.3 Code Designs -- 19.4 Applications -- 19.5 Conclusions -- References. -- 20. Network Coding for Sensor Networks (Christina Fragouli) -- 20.1 Introduction -- 20.2 How Can We Implement Network Coding in a Practical Sensor Network? -- 20.3 Data Collection and Coupon Collector Problem -- 20.4 Distributed Storage and Sensor Network Data Persistence -- 20.5 Decentralized Operation and Untuned Radios -- 20.6 Broadcasting and Multipath Diversity -- 20.7 Network, Channel and Source Coding -- 20.8 Identity-Aware Sensor Networks -- 20.9 Discussion -- Acknowledgments -- References. -- 21. Information-Theoretic Studies of Wireless Sensor Networks (Liang-Liang Xie and P. R. Kumar) -- 21.1 Introduction -- 21.2 Information-Theoretic Studies -- 21.3 Relay Schemes -- 21.4 Wireless Network Coding -- 21.5 Concluding Remarks -- Acknowledgments -- References. -- PART IV: NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS -- 22. Distributed Adaptive Learning Mechanisms (Ali H. Sayed and Federico S. Cattivelli) -- 22.1 Introduction -- 22.2 Motivation -- 22.3 Incremental Adaptive Solutions -- 22.4 Diffusion Adaptive Solutions -- 22.5 Concluding Remarks -- Acknowledgments -- References -- 23. Routing for Statistical Inference in Sensor Networks (A. Anandkumar, A. Ephremides, A. Swami and L. Tong) -- 23.1 Introduction -- 23.2 Spatial Data Correlation -- 23.3 Statistical Inference of Markov Random Fields -- 23.4 Optimal Routing for Inference with Local Processing -- 23.5 Conclusion and Future Work -- 23.6 Bibliographic Notes -- References. -- 24. Spectral Estimation in Cognitive Radios (Behrouz Farhang-Boroujeny) -- 24.1 Filter Bank Formulation of Spectral Estimators -- 24.2 Polyphase Realization of Uniform Filter Banks.
24.3 Periodogram Spectral Estimator -- 24.4 Multitaper Spectral Estimator -- 24.5 Filter Bank Spectral Estimator -- 24.6 Distributed Spectrum Sensing -- 24.7 Discussion -- Appendix A: Effective Degree of Freedom -- Appendix B: Explanation to the Results of Table 24.1 -- References -- 25. Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks (Azadeh Kushki and Kostas N. Plataniotis) -- 25.1 Introduction -- 25.2 WLAN Positioning Architectures -- 25.3 Signal Models -- 25.4 Zero-Memory Positioning -- 25.5 Dynamic Positioning Systems -- 25.6 Cognition and Feedback -- 25.7 Tracking Example -- 25.8 Conclusions -- References -- 26. Reconfigurable Self-Activating Ion-Channel-Based Biosensors Vikram Krishnamurthy and Bruce Cornell) -- 26.1 Introduction -- 26.2 Biosensors Built of Ion Channels -- 26.3 Joint Input Excitation and Concentration Classification for Biosensor -- 26.4 Decentralized Deployment of Dense Network of Biosensors -- 26.5 Discussion and Extensions -- References. -- 27. Biochemical Transport Modeling, Estimation and Detection in Realistic Environments (Mathias Ortner and Arye Nehorai ) -- 27.1 Introduction -- 27.2 Physical and Statistical Models -- 27.3 Transport Modeling Using Monte Carlo Approximation -- 27.4 Localizing the Source(s) -- 27.5 Sequential Detection -- 27.6 Conclusion -- References -- 28. Security and Privacy for Sensor Networks (Wade Trappe, Peng Ning and Adrian Perrig) -- 28.1 Introduction -- 28.2 Security and Privacy Challenges -- 28.3 Ensuring Integrity of Measurement Process -- 28.4 Availability Attacks against the Wireless Link -- 28.5 Ensuring Privacy of Routing Contexts -- 28.6 Conclusion -- References -- Index.
Record Nr. UNINA-9910140619803321
Haykin Simon S. <1931->  
[Piscataway, New Jersey] : , : IEEE, , c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Handbook on array processing and sensor networks / / [edited by] Simon Haykin, K.J. Ray Liu
Handbook on array processing and sensor networks / / [edited by] Simon Haykin, K.J. Ray Liu
Autore Haykin Simon S. <1931->
Edizione [1st edition]
Pubbl/distr/stampa [Piscataway, New Jersey] : , : IEEE, , c2009
Descrizione fisica 1 online resource (924 p.)
Disciplina 621.382/4
621.3822
621.3824
Altri autori (Persone) LiuK. J. Ray
HaykinSimon S
Collana Adaptive and learning systems for signal processing, communications and control series
Soggetto topico Sensor networks
Antenna arrays
Array processors
ISBN 1-282-54932-4
9786612549328
1-61344-501-6
0-470-48706-2
0-470-48705-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface (Simon Haykin and K. J. Ray Liu) -- Contributors -- Introduction (Simon Haykin) -- PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING -- 1. Wavefields. (Alfred Hanssen) -- 1.1 Introduction -- 1.2 Harmonizable Stochastic Processes -- 1.3 Stochastic Wavefields -- 1.4 Wave Dispersion -- 1.5 Conclusions -- 1.6 Acknowledgements -- References. -- 2. Spatial Spectrum Estimation (Petar M. Djuri) -- 2.1 Introduction -- 2.2 Fundamentals -- 2.3 Temporal Spectrum Estimation -- 2.4 Spatial Spectrum Estimation -- 2.5 Final Remarks -- References. -- 3. MIMO Radio Propagation (Tricia J. Willink) -- 3.1 Introduction -- 3.2 Space-Time Propagation Environment -- 3.3 Propagation Models -- 3.4 Measured Channel Characteristics -- 3.5 Stationarity -- 3.6 Summary -- References. -- 4. Robustness Issues in Sensor Array Processing (Alex B. Gershman) -- 4.1 Introduction -- 4.2 Direction-of-Arrival Estimation -- 4.3 Adaptive Beamforming -- 4.4 Conclusions -- Acknowledgments -- References. -- 5. Wireless Communication and Sensing in Multipath Environments Using Multiantenna Transceivers (Akbar M. Sayeed and Thiagarajan Sivanadyan) -- 5.1 Introduction and Overview -- 5.2 Multipath Wireless Channel Modeling in Time, Frequency and Space -- 5.3 Point-to-Point MIMO Wireless Communication Systems -- 5.4 Active Wireless Sensing with Wideband MIMO Transceivers -- 5.5 Concluding Remarks -- References -- PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF ARRAY SIGNAL PROCESSING. -- 6. Implicit Training and Array Processing for Digital Communication Systems (Aldo G. Orozco-Lugo, Mauricio Lara, and Desmond C. McLernon) -- 6.1 Introduction -- 6.2 Classification of Implicit Training Methods -- 6.3 IT-Based Estimation for a Single User -- 6.4 IT-Based Estimation for Multiple Users Exploiting Array Processing: Continuous Transmission -- 6.5 IT-Based Estimation for Multiple Users Exploiting Array Processing: Packet Transmission -- 6.6 Open Research Problems -- Acknowledgments -- References -- 7. Unitary Design of Radar Waveform Diversity Sets (Michael D. Zoltowski, Tariq R. Qureshi, Robert Calderbank, and Bill Moran).
7.1 Introduction -- 7.2 2 x 2 Space-Time Diversity Waveform Design -- 7.3 4 x 4 Space-Time Diversity Waveform Design -- 7.4 Waveform Families Based on Kronecker Products -- 7.5 Introduction to Data-Dependent Waveform Design -- 7.6 3 x 3 and 6 x 6 Waveform Scheduling -- 7.7 Summary -- References. -- 8. Acoustic Array Processing for Speech Enhancement (Markus Buck, Eberhard H Ansler, Mohamed Krini, Gerhard Schmidt and Tobias Wolff) -- 8.1 Introduction -- 8.2 Signal Processing in the Subband Domain -- 8.3 Multichannel Echo Cancelation -- 8.4 Speaker Localization -- 8.5 Beamforming -- 8.6 Sensor Calibration -- 8.7 Postprocessing -- 8.8 Conclusions -- References -- 9. Acoustic Beamforming for Hearing Aid Applications (Simon Doclo, Sharon Gannot, Marc Moonen and Ann Spriet) -- 9.1. Introduction -- 9.2. Overview of noise reduction techniques -- 9.3. Monaural beamforming -- 9.4. Binaural beamforming -- 9.5. Conclusion -- 10. Undetermined Blind Source Separation Using Acoustic Arrays (Shoji Makino, Shoko Araki, Stefan Winter and Hiroshi Sawada) -- 10.1 Introduction -- 10.2 Underdetermined Blind Source Separation of Speeches in Reverberant Environments -- 10.3 Sparseness of Speech Sources -- 10.4 Binary Mask Approach to Underdetermined BSS -- 10.5 MAP-Based Two-Stage Approach to Underdetermined BSS -- 10.6 Experimental Comparison with Binary Mask Approach and MAP-Based Two-Stage Approach -- 10.7 Concluding Remarks -- References -- 11. Array Processing in Astronomy (Douglas C.-J. Bock) -- 11.1 Introduction -- 11.2 Correlation Arrays -- 11.3 Aperture Plane Phased Arrays -- 11.4 Future Directions -- 11.5 Conclusion -- References. -- 12. Digital 3D/4D Ultrasound Imaging Array (Stergios Stergiopoulos) -- 12.1 Background -- 12.2 Next Generation 3D/4D Ultrasound Imaging Technology -- 12.3 Computing Architecture and Implementation Issues -- 12.4 An Experimental Planar Array Ultrasound Imaging System -- 12.5 Conclusion -- References -- PART III: FUNDAMENTAL ISSUES IN DISTRIBUTED SENSOR NETWORKS.
13. Self-Localization of Sensor Networks (Josh N. Ash and Randolph L. Moses) -- 13.1 Introduction -- 13.2 Measurement Types and Performance Bounds -- 13.3 Localization Algorithms -- 13.4 Relative and Transformation Error Decomposition -- 13.5 Conclusions -- References. -- 14. Multitarget Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo (Tom Vercauteren and Xiaodong Wang) -- 14.1 Introduction -- 14.2 System Description and Problem Formulation -- 14.3 Sequential Monte Carlo Methods -- 14.4 Joint Single-Target Tracking and Classification -- 14.5 Multiple-Target Tracking and Classification -- 14.6 Sensor Selection -- 14.7 Simulation Results -- Conclusion -- Appendix: Derviations of (14.38 and (14.40) -- References -- 15. Energy-Efficient Decentralized Estimation (Jin-Jun Xiao, Shuguang Cui and Zhi-Quan Luo) -- 15.5 Introduction -- 15.2 System Model -- 15.3 Digital Approaches -- 15.4 Analog Approaches -- 15.5 Analog versus Digital -- 15.6 Extension to Vector Model -- 15.7 Concluding Remarks -- Acknowledgments -- References. -- 16. Sensor Data Fusion with Application to Multitarget Tracking (R. Tharmarasa, K. Punithakumar, T. Kirubarajan and Y. Bar-Shalom) -- 16.1 Introduction -- 16.2 Tracking Filters -- 16.3 Data Association -- 16.4 Out-of-Sequence Measurements -- 16.5 Results with Real Data -- 16.6 Summary -- References. -- 17. Distributed Algorithms in Sensor Networks (Usman A. Khan, Soummya Kar and Jos A A Moura) -- 17.1 Introduction -- 17.2 Preliminaries -- 17.3 Distributed Detection -- 17.4 Consensus Algorithms -- 17.5 Zero-Dimension (Average) Consensus -- 17.6 Consensus in Higher Dimensions -- 17.7 Leader-Follower (Type) Algorithms -- 17.8 Localization in Sensor Networks -- 17.9 Linear System of Equations: Distributed Algorithm -- 17.10 Conclusions -- References. -- 18. Cooperative Sensor Communications (Ahmed K. Sadek, Weifeng Su and K. J. Ray Liu) -- 18.1 Introduction -- 18.2 Cooperative Relay Protocols -- 18.3 SER Analysis and Optimal Power Allocation.
18.4 Energy Efficiency in Cooperative Sensor Networks -- 18.5 Experimental Results -- 18.6 Conclusions -- References. -- 19. Distributed Source Coding (Zixiang Xiong, Angelos D. Liveris and Yang Yang) -- 19.1 Introduction -- 19.2 Theoretical Background -- 19.3 Code Designs -- 19.4 Applications -- 19.5 Conclusions -- References. -- 20. Network Coding for Sensor Networks (Christina Fragouli) -- 20.1 Introduction -- 20.2 How Can We Implement Network Coding in a Practical Sensor Network? -- 20.3 Data Collection and Coupon Collector Problem -- 20.4 Distributed Storage and Sensor Network Data Persistence -- 20.5 Decentralized Operation and Untuned Radios -- 20.6 Broadcasting and Multipath Diversity -- 20.7 Network, Channel and Source Coding -- 20.8 Identity-Aware Sensor Networks -- 20.9 Discussion -- Acknowledgments -- References. -- 21. Information-Theoretic Studies of Wireless Sensor Networks (Liang-Liang Xie and P. R. Kumar) -- 21.1 Introduction -- 21.2 Information-Theoretic Studies -- 21.3 Relay Schemes -- 21.4 Wireless Network Coding -- 21.5 Concluding Remarks -- Acknowledgments -- References. -- PART IV: NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS -- 22. Distributed Adaptive Learning Mechanisms (Ali H. Sayed and Federico S. Cattivelli) -- 22.1 Introduction -- 22.2 Motivation -- 22.3 Incremental Adaptive Solutions -- 22.4 Diffusion Adaptive Solutions -- 22.5 Concluding Remarks -- Acknowledgments -- References -- 23. Routing for Statistical Inference in Sensor Networks (A. Anandkumar, A. Ephremides, A. Swami and L. Tong) -- 23.1 Introduction -- 23.2 Spatial Data Correlation -- 23.3 Statistical Inference of Markov Random Fields -- 23.4 Optimal Routing for Inference with Local Processing -- 23.5 Conclusion and Future Work -- 23.6 Bibliographic Notes -- References. -- 24. Spectral Estimation in Cognitive Radios (Behrouz Farhang-Boroujeny) -- 24.1 Filter Bank Formulation of Spectral Estimators -- 24.2 Polyphase Realization of Uniform Filter Banks.
24.3 Periodogram Spectral Estimator -- 24.4 Multitaper Spectral Estimator -- 24.5 Filter Bank Spectral Estimator -- 24.6 Distributed Spectrum Sensing -- 24.7 Discussion -- Appendix A: Effective Degree of Freedom -- Appendix B: Explanation to the Results of Table 24.1 -- References -- 25. Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks (Azadeh Kushki and Kostas N. Plataniotis) -- 25.1 Introduction -- 25.2 WLAN Positioning Architectures -- 25.3 Signal Models -- 25.4 Zero-Memory Positioning -- 25.5 Dynamic Positioning Systems -- 25.6 Cognition and Feedback -- 25.7 Tracking Example -- 25.8 Conclusions -- References -- 26. Reconfigurable Self-Activating Ion-Channel-Based Biosensors Vikram Krishnamurthy and Bruce Cornell) -- 26.1 Introduction -- 26.2 Biosensors Built of Ion Channels -- 26.3 Joint Input Excitation and Concentration Classification for Biosensor -- 26.4 Decentralized Deployment of Dense Network of Biosensors -- 26.5 Discussion and Extensions -- References. -- 27. Biochemical Transport Modeling, Estimation and Detection in Realistic Environments (Mathias Ortner and Arye Nehorai ) -- 27.1 Introduction -- 27.2 Physical and Statistical Models -- 27.3 Transport Modeling Using Monte Carlo Approximation -- 27.4 Localizing the Source(s) -- 27.5 Sequential Detection -- 27.6 Conclusion -- References -- 28. Security and Privacy for Sensor Networks (Wade Trappe, Peng Ning and Adrian Perrig) -- 28.1 Introduction -- 28.2 Security and Privacy Challenges -- 28.3 Ensuring Integrity of Measurement Process -- 28.4 Availability Attacks against the Wireless Link -- 28.5 Ensuring Privacy of Routing Contexts -- 28.6 Conclusion -- References -- Index.
Record Nr. UNISA-996204858203316
Haykin Simon S. <1931->  
[Piscataway, New Jersey] : , : IEEE, , c2009
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Handbook on array processing and sensor networks / / [edited by] Simon Haykin, K.J. Ray Liu
Handbook on array processing and sensor networks / / [edited by] Simon Haykin, K.J. Ray Liu
Autore Haykin Simon S. <1931->
Edizione [1st edition]
Pubbl/distr/stampa [Piscataway, New Jersey] : , : IEEE, , c2009
Descrizione fisica 1 online resource (924 p.)
Disciplina 621.382/4
621.3822
621.3824
Altri autori (Persone) LiuK. J. Ray
HaykinSimon S
Collana Adaptive and learning systems for signal processing, communications and control series
Soggetto topico Sensor networks
Antenna arrays
Array processors
ISBN 1-282-54932-4
9786612549328
1-61344-501-6
0-470-48706-2
0-470-48705-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface (Simon Haykin and K. J. Ray Liu) -- Contributors -- Introduction (Simon Haykin) -- PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING -- 1. Wavefields. (Alfred Hanssen) -- 1.1 Introduction -- 1.2 Harmonizable Stochastic Processes -- 1.3 Stochastic Wavefields -- 1.4 Wave Dispersion -- 1.5 Conclusions -- 1.6 Acknowledgements -- References. -- 2. Spatial Spectrum Estimation (Petar M. Djuri) -- 2.1 Introduction -- 2.2 Fundamentals -- 2.3 Temporal Spectrum Estimation -- 2.4 Spatial Spectrum Estimation -- 2.5 Final Remarks -- References. -- 3. MIMO Radio Propagation (Tricia J. Willink) -- 3.1 Introduction -- 3.2 Space-Time Propagation Environment -- 3.3 Propagation Models -- 3.4 Measured Channel Characteristics -- 3.5 Stationarity -- 3.6 Summary -- References. -- 4. Robustness Issues in Sensor Array Processing (Alex B. Gershman) -- 4.1 Introduction -- 4.2 Direction-of-Arrival Estimation -- 4.3 Adaptive Beamforming -- 4.4 Conclusions -- Acknowledgments -- References. -- 5. Wireless Communication and Sensing in Multipath Environments Using Multiantenna Transceivers (Akbar M. Sayeed and Thiagarajan Sivanadyan) -- 5.1 Introduction and Overview -- 5.2 Multipath Wireless Channel Modeling in Time, Frequency and Space -- 5.3 Point-to-Point MIMO Wireless Communication Systems -- 5.4 Active Wireless Sensing with Wideband MIMO Transceivers -- 5.5 Concluding Remarks -- References -- PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF ARRAY SIGNAL PROCESSING. -- 6. Implicit Training and Array Processing for Digital Communication Systems (Aldo G. Orozco-Lugo, Mauricio Lara, and Desmond C. McLernon) -- 6.1 Introduction -- 6.2 Classification of Implicit Training Methods -- 6.3 IT-Based Estimation for a Single User -- 6.4 IT-Based Estimation for Multiple Users Exploiting Array Processing: Continuous Transmission -- 6.5 IT-Based Estimation for Multiple Users Exploiting Array Processing: Packet Transmission -- 6.6 Open Research Problems -- Acknowledgments -- References -- 7. Unitary Design of Radar Waveform Diversity Sets (Michael D. Zoltowski, Tariq R. Qureshi, Robert Calderbank, and Bill Moran).
7.1 Introduction -- 7.2 2 x 2 Space-Time Diversity Waveform Design -- 7.3 4 x 4 Space-Time Diversity Waveform Design -- 7.4 Waveform Families Based on Kronecker Products -- 7.5 Introduction to Data-Dependent Waveform Design -- 7.6 3 x 3 and 6 x 6 Waveform Scheduling -- 7.7 Summary -- References. -- 8. Acoustic Array Processing for Speech Enhancement (Markus Buck, Eberhard H Ansler, Mohamed Krini, Gerhard Schmidt and Tobias Wolff) -- 8.1 Introduction -- 8.2 Signal Processing in the Subband Domain -- 8.3 Multichannel Echo Cancelation -- 8.4 Speaker Localization -- 8.5 Beamforming -- 8.6 Sensor Calibration -- 8.7 Postprocessing -- 8.8 Conclusions -- References -- 9. Acoustic Beamforming for Hearing Aid Applications (Simon Doclo, Sharon Gannot, Marc Moonen and Ann Spriet) -- 9.1. Introduction -- 9.2. Overview of noise reduction techniques -- 9.3. Monaural beamforming -- 9.4. Binaural beamforming -- 9.5. Conclusion -- 10. Undetermined Blind Source Separation Using Acoustic Arrays (Shoji Makino, Shoko Araki, Stefan Winter and Hiroshi Sawada) -- 10.1 Introduction -- 10.2 Underdetermined Blind Source Separation of Speeches in Reverberant Environments -- 10.3 Sparseness of Speech Sources -- 10.4 Binary Mask Approach to Underdetermined BSS -- 10.5 MAP-Based Two-Stage Approach to Underdetermined BSS -- 10.6 Experimental Comparison with Binary Mask Approach and MAP-Based Two-Stage Approach -- 10.7 Concluding Remarks -- References -- 11. Array Processing in Astronomy (Douglas C.-J. Bock) -- 11.1 Introduction -- 11.2 Correlation Arrays -- 11.3 Aperture Plane Phased Arrays -- 11.4 Future Directions -- 11.5 Conclusion -- References. -- 12. Digital 3D/4D Ultrasound Imaging Array (Stergios Stergiopoulos) -- 12.1 Background -- 12.2 Next Generation 3D/4D Ultrasound Imaging Technology -- 12.3 Computing Architecture and Implementation Issues -- 12.4 An Experimental Planar Array Ultrasound Imaging System -- 12.5 Conclusion -- References -- PART III: FUNDAMENTAL ISSUES IN DISTRIBUTED SENSOR NETWORKS.
13. Self-Localization of Sensor Networks (Josh N. Ash and Randolph L. Moses) -- 13.1 Introduction -- 13.2 Measurement Types and Performance Bounds -- 13.3 Localization Algorithms -- 13.4 Relative and Transformation Error Decomposition -- 13.5 Conclusions -- References. -- 14. Multitarget Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo (Tom Vercauteren and Xiaodong Wang) -- 14.1 Introduction -- 14.2 System Description and Problem Formulation -- 14.3 Sequential Monte Carlo Methods -- 14.4 Joint Single-Target Tracking and Classification -- 14.5 Multiple-Target Tracking and Classification -- 14.6 Sensor Selection -- 14.7 Simulation Results -- Conclusion -- Appendix: Derviations of (14.38 and (14.40) -- References -- 15. Energy-Efficient Decentralized Estimation (Jin-Jun Xiao, Shuguang Cui and Zhi-Quan Luo) -- 15.5 Introduction -- 15.2 System Model -- 15.3 Digital Approaches -- 15.4 Analog Approaches -- 15.5 Analog versus Digital -- 15.6 Extension to Vector Model -- 15.7 Concluding Remarks -- Acknowledgments -- References. -- 16. Sensor Data Fusion with Application to Multitarget Tracking (R. Tharmarasa, K. Punithakumar, T. Kirubarajan and Y. Bar-Shalom) -- 16.1 Introduction -- 16.2 Tracking Filters -- 16.3 Data Association -- 16.4 Out-of-Sequence Measurements -- 16.5 Results with Real Data -- 16.6 Summary -- References. -- 17. Distributed Algorithms in Sensor Networks (Usman A. Khan, Soummya Kar and Jos A A Moura) -- 17.1 Introduction -- 17.2 Preliminaries -- 17.3 Distributed Detection -- 17.4 Consensus Algorithms -- 17.5 Zero-Dimension (Average) Consensus -- 17.6 Consensus in Higher Dimensions -- 17.7 Leader-Follower (Type) Algorithms -- 17.8 Localization in Sensor Networks -- 17.9 Linear System of Equations: Distributed Algorithm -- 17.10 Conclusions -- References. -- 18. Cooperative Sensor Communications (Ahmed K. Sadek, Weifeng Su and K. J. Ray Liu) -- 18.1 Introduction -- 18.2 Cooperative Relay Protocols -- 18.3 SER Analysis and Optimal Power Allocation.
18.4 Energy Efficiency in Cooperative Sensor Networks -- 18.5 Experimental Results -- 18.6 Conclusions -- References. -- 19. Distributed Source Coding (Zixiang Xiong, Angelos D. Liveris and Yang Yang) -- 19.1 Introduction -- 19.2 Theoretical Background -- 19.3 Code Designs -- 19.4 Applications -- 19.5 Conclusions -- References. -- 20. Network Coding for Sensor Networks (Christina Fragouli) -- 20.1 Introduction -- 20.2 How Can We Implement Network Coding in a Practical Sensor Network? -- 20.3 Data Collection and Coupon Collector Problem -- 20.4 Distributed Storage and Sensor Network Data Persistence -- 20.5 Decentralized Operation and Untuned Radios -- 20.6 Broadcasting and Multipath Diversity -- 20.7 Network, Channel and Source Coding -- 20.8 Identity-Aware Sensor Networks -- 20.9 Discussion -- Acknowledgments -- References. -- 21. Information-Theoretic Studies of Wireless Sensor Networks (Liang-Liang Xie and P. R. Kumar) -- 21.1 Introduction -- 21.2 Information-Theoretic Studies -- 21.3 Relay Schemes -- 21.4 Wireless Network Coding -- 21.5 Concluding Remarks -- Acknowledgments -- References. -- PART IV: NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS -- 22. Distributed Adaptive Learning Mechanisms (Ali H. Sayed and Federico S. Cattivelli) -- 22.1 Introduction -- 22.2 Motivation -- 22.3 Incremental Adaptive Solutions -- 22.4 Diffusion Adaptive Solutions -- 22.5 Concluding Remarks -- Acknowledgments -- References -- 23. Routing for Statistical Inference in Sensor Networks (A. Anandkumar, A. Ephremides, A. Swami and L. Tong) -- 23.1 Introduction -- 23.2 Spatial Data Correlation -- 23.3 Statistical Inference of Markov Random Fields -- 23.4 Optimal Routing for Inference with Local Processing -- 23.5 Conclusion and Future Work -- 23.6 Bibliographic Notes -- References. -- 24. Spectral Estimation in Cognitive Radios (Behrouz Farhang-Boroujeny) -- 24.1 Filter Bank Formulation of Spectral Estimators -- 24.2 Polyphase Realization of Uniform Filter Banks.
24.3 Periodogram Spectral Estimator -- 24.4 Multitaper Spectral Estimator -- 24.5 Filter Bank Spectral Estimator -- 24.6 Distributed Spectrum Sensing -- 24.7 Discussion -- Appendix A: Effective Degree of Freedom -- Appendix B: Explanation to the Results of Table 24.1 -- References -- 25. Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks (Azadeh Kushki and Kostas N. Plataniotis) -- 25.1 Introduction -- 25.2 WLAN Positioning Architectures -- 25.3 Signal Models -- 25.4 Zero-Memory Positioning -- 25.5 Dynamic Positioning Systems -- 25.6 Cognition and Feedback -- 25.7 Tracking Example -- 25.8 Conclusions -- References -- 26. Reconfigurable Self-Activating Ion-Channel-Based Biosensors Vikram Krishnamurthy and Bruce Cornell) -- 26.1 Introduction -- 26.2 Biosensors Built of Ion Channels -- 26.3 Joint Input Excitation and Concentration Classification for Biosensor -- 26.4 Decentralized Deployment of Dense Network of Biosensors -- 26.5 Discussion and Extensions -- References. -- 27. Biochemical Transport Modeling, Estimation and Detection in Realistic Environments (Mathias Ortner and Arye Nehorai ) -- 27.1 Introduction -- 27.2 Physical and Statistical Models -- 27.3 Transport Modeling Using Monte Carlo Approximation -- 27.4 Localizing the Source(s) -- 27.5 Sequential Detection -- 27.6 Conclusion -- References -- 28. Security and Privacy for Sensor Networks (Wade Trappe, Peng Ning and Adrian Perrig) -- 28.1 Introduction -- 28.2 Security and Privacy Challenges -- 28.3 Ensuring Integrity of Measurement Process -- 28.4 Availability Attacks against the Wireless Link -- 28.5 Ensuring Privacy of Routing Contexts -- 28.6 Conclusion -- References -- Index.
Record Nr. UNINA-9910830400203321
Haykin Simon S. <1931->  
[Piscataway, New Jersey] : , : IEEE, , c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Handbook on array processing and sensor networks / / Simon S. Haykin, K.J. Ray Liu
Handbook on array processing and sensor networks / / Simon S. Haykin, K.J. Ray Liu
Autore Haykin Simon S. <1931->
Edizione [1st edition]
Pubbl/distr/stampa Hoboken, N.J., : John Wiley & Sons, 2009
Descrizione fisica 1 online resource (924 p.)
Disciplina 621.382/4
Altri autori (Persone) LiuK. J. Ray <1961->
Collana Adaptive and learning systems for signal processing, communications and control series
Soggetto topico Sensor networks
Antenna arrays
Array processors
ISBN 9786612549328
9781282549326
1282549324
9781613445013
1613445016
9780470487068
0470487062
9780470487051
0470487054
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface (Simon Haykin and K. J. Ray Liu) -- Contributors -- Introduction (Simon Haykin) -- PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING -- 1. Wavefields. (Alfred Hanssen) -- 1.1 Introduction -- 1.2 Harmonizable Stochastic Processes -- 1.3 Stochastic Wavefields -- 1.4 Wave Dispersion -- 1.5 Conclusions -- 1.6 Acknowledgements -- References. -- 2. Spatial Spectrum Estimation (Petar M. Djuri) -- 2.1 Introduction -- 2.2 Fundamentals -- 2.3 Temporal Spectrum Estimation -- 2.4 Spatial Spectrum Estimation -- 2.5 Final Remarks -- References. -- 3. MIMO Radio Propagation (Tricia J. Willink) -- 3.1 Introduction -- 3.2 Space-Time Propagation Environment -- 3.3 Propagation Models -- 3.4 Measured Channel Characteristics -- 3.5 Stationarity -- 3.6 Summary -- References. -- 4. Robustness Issues in Sensor Array Processing (Alex B. Gershman) -- 4.1 Introduction -- 4.2 Direction-of-Arrival Estimation -- 4.3 Adaptive Beamforming -- 4.4 Conclusions -- Acknowledgments -- References. -- 5. Wireless Communication and Sensing in Multipath Environments Using Multiantenna Transceivers (Akbar M. Sayeed and Thiagarajan Sivanadyan) -- 5.1 Introduction and Overview -- 5.2 Multipath Wireless Channel Modeling in Time, Frequency and Space -- 5.3 Point-to-Point MIMO Wireless Communication Systems -- 5.4 Active Wireless Sensing with Wideband MIMO Transceivers -- 5.5 Concluding Remarks -- References -- PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF ARRAY SIGNAL PROCESSING. -- 6. Implicit Training and Array Processing for Digital Communication Systems (Aldo G. Orozco-Lugo, Mauricio Lara, and Desmond C. McLernon) -- 6.1 Introduction -- 6.2 Classification of Implicit Training Methods -- 6.3 IT-Based Estimation for a Single User -- 6.4 IT-Based Estimation for Multiple Users Exploiting Array Processing: Continuous Transmission -- 6.5 IT-Based Estimation for Multiple Users Exploiting Array Processing: Packet Transmission -- 6.6 Open Research Problems -- Acknowledgments -- References -- 7. Unitary Design of Radar Waveform Diversity Sets (Michael D. Zoltowski, Tariq R. Qureshi, Robert Calderbank, and Bill Moran).
7.1 Introduction -- 7.2 2 x 2 Space-Time Diversity Waveform Design -- 7.3 4 x 4 Space-Time Diversity Waveform Design -- 7.4 Waveform Families Based on Kronecker Products -- 7.5 Introduction to Data-Dependent Waveform Design -- 7.6 3 x 3 and 6 x 6 Waveform Scheduling -- 7.7 Summary -- References. -- 8. Acoustic Array Processing for Speech Enhancement (Markus Buck, Eberhard H Ansler, Mohamed Krini, Gerhard Schmidt and Tobias Wolff) -- 8.1 Introduction -- 8.2 Signal Processing in the Subband Domain -- 8.3 Multichannel Echo Cancelation -- 8.4 Speaker Localization -- 8.5 Beamforming -- 8.6 Sensor Calibration -- 8.7 Postprocessing -- 8.8 Conclusions -- References -- 9. Acoustic Beamforming for Hearing Aid Applications (Simon Doclo, Sharon Gannot, Marc Moonen and Ann Spriet) -- 9.1. Introduction -- 9.2. Overview of noise reduction techniques -- 9.3. Monaural beamforming -- 9.4. Binaural beamforming -- 9.5. Conclusion -- 10. Undetermined Blind Source Separation Using Acoustic Arrays (Shoji Makino, Shoko Araki, Stefan Winter and Hiroshi Sawada) -- 10.1 Introduction -- 10.2 Underdetermined Blind Source Separation of Speeches in Reverberant Environments -- 10.3 Sparseness of Speech Sources -- 10.4 Binary Mask Approach to Underdetermined BSS -- 10.5 MAP-Based Two-Stage Approach to Underdetermined BSS -- 10.6 Experimental Comparison with Binary Mask Approach and MAP-Based Two-Stage Approach -- 10.7 Concluding Remarks -- References -- 11. Array Processing in Astronomy (Douglas C.-J. Bock) -- 11.1 Introduction -- 11.2 Correlation Arrays -- 11.3 Aperture Plane Phased Arrays -- 11.4 Future Directions -- 11.5 Conclusion -- References. -- 12. Digital 3D/4D Ultrasound Imaging Array (Stergios Stergiopoulos) -- 12.1 Background -- 12.2 Next Generation 3D/4D Ultrasound Imaging Technology -- 12.3 Computing Architecture and Implementation Issues -- 12.4 An Experimental Planar Array Ultrasound Imaging System -- 12.5 Conclusion -- References -- PART III: FUNDAMENTAL ISSUES IN DISTRIBUTED SENSOR NETWORKS.
13. Self-Localization of Sensor Networks (Josh N. Ash and Randolph L. Moses) -- 13.1 Introduction -- 13.2 Measurement Types and Performance Bounds -- 13.3 Localization Algorithms -- 13.4 Relative and Transformation Error Decomposition -- 13.5 Conclusions -- References. -- 14. Multitarget Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo (Tom Vercauteren and Xiaodong Wang) -- 14.1 Introduction -- 14.2 System Description and Problem Formulation -- 14.3 Sequential Monte Carlo Methods -- 14.4 Joint Single-Target Tracking and Classification -- 14.5 Multiple-Target Tracking and Classification -- 14.6 Sensor Selection -- 14.7 Simulation Results -- Conclusion -- Appendix: Derviations of (14.38 and (14.40) -- References -- 15. Energy-Efficient Decentralized Estimation (Jin-Jun Xiao, Shuguang Cui and Zhi-Quan Luo) -- 15.5 Introduction -- 15.2 System Model -- 15.3 Digital Approaches -- 15.4 Analog Approaches -- 15.5 Analog versus Digital -- 15.6 Extension to Vector Model -- 15.7 Concluding Remarks -- Acknowledgments -- References. -- 16. Sensor Data Fusion with Application to Multitarget Tracking (R. Tharmarasa, K. Punithakumar, T. Kirubarajan and Y. Bar-Shalom) -- 16.1 Introduction -- 16.2 Tracking Filters -- 16.3 Data Association -- 16.4 Out-of-Sequence Measurements -- 16.5 Results with Real Data -- 16.6 Summary -- References. -- 17. Distributed Algorithms in Sensor Networks (Usman A. Khan, Soummya Kar and Jos A A Moura) -- 17.1 Introduction -- 17.2 Preliminaries -- 17.3 Distributed Detection -- 17.4 Consensus Algorithms -- 17.5 Zero-Dimension (Average) Consensus -- 17.6 Consensus in Higher Dimensions -- 17.7 Leader-Follower (Type) Algorithms -- 17.8 Localization in Sensor Networks -- 17.9 Linear System of Equations: Distributed Algorithm -- 17.10 Conclusions -- References. -- 18. Cooperative Sensor Communications (Ahmed K. Sadek, Weifeng Su and K. J. Ray Liu) -- 18.1 Introduction -- 18.2 Cooperative Relay Protocols -- 18.3 SER Analysis and Optimal Power Allocation.
18.4 Energy Efficiency in Cooperative Sensor Networks -- 18.5 Experimental Results -- 18.6 Conclusions -- References. -- 19. Distributed Source Coding (Zixiang Xiong, Angelos D. Liveris and Yang Yang) -- 19.1 Introduction -- 19.2 Theoretical Background -- 19.3 Code Designs -- 19.4 Applications -- 19.5 Conclusions -- References. -- 20. Network Coding for Sensor Networks (Christina Fragouli) -- 20.1 Introduction -- 20.2 How Can We Implement Network Coding in a Practical Sensor Network? -- 20.3 Data Collection and Coupon Collector Problem -- 20.4 Distributed Storage and Sensor Network Data Persistence -- 20.5 Decentralized Operation and Untuned Radios -- 20.6 Broadcasting and Multipath Diversity -- 20.7 Network, Channel and Source Coding -- 20.8 Identity-Aware Sensor Networks -- 20.9 Discussion -- Acknowledgments -- References. -- 21. Information-Theoretic Studies of Wireless Sensor Networks (Liang-Liang Xie and P. R. Kumar) -- 21.1 Introduction -- 21.2 Information-Theoretic Studies -- 21.3 Relay Schemes -- 21.4 Wireless Network Coding -- 21.5 Concluding Remarks -- Acknowledgments -- References. -- PART IV: NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS -- 22. Distributed Adaptive Learning Mechanisms (Ali H. Sayed and Federico S. Cattivelli) -- 22.1 Introduction -- 22.2 Motivation -- 22.3 Incremental Adaptive Solutions -- 22.4 Diffusion Adaptive Solutions -- 22.5 Concluding Remarks -- Acknowledgments -- References -- 23. Routing for Statistical Inference in Sensor Networks (A. Anandkumar, A. Ephremides, A. Swami and L. Tong) -- 23.1 Introduction -- 23.2 Spatial Data Correlation -- 23.3 Statistical Inference of Markov Random Fields -- 23.4 Optimal Routing for Inference with Local Processing -- 23.5 Conclusion and Future Work -- 23.6 Bibliographic Notes -- References. -- 24. Spectral Estimation in Cognitive Radios (Behrouz Farhang-Boroujeny) -- 24.1 Filter Bank Formulation of Spectral Estimators -- 24.2 Polyphase Realization of Uniform Filter Banks.
24.3 Periodogram Spectral Estimator -- 24.4 Multitaper Spectral Estimator -- 24.5 Filter Bank Spectral Estimator -- 24.6 Distributed Spectrum Sensing -- 24.7 Discussion -- Appendix A: Effective Degree of Freedom -- Appendix B: Explanation to the Results of Table 24.1 -- References -- 25. Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks (Azadeh Kushki and Kostas N. Plataniotis) -- 25.1 Introduction -- 25.2 WLAN Positioning Architectures -- 25.3 Signal Models -- 25.4 Zero-Memory Positioning -- 25.5 Dynamic Positioning Systems -- 25.6 Cognition and Feedback -- 25.7 Tracking Example -- 25.8 Conclusions -- References -- 26. Reconfigurable Self-Activating Ion-Channel-Based Biosensors Vikram Krishnamurthy and Bruce Cornell) -- 26.1 Introduction -- 26.2 Biosensors Built of Ion Channels -- 26.3 Joint Input Excitation and Concentration Classification for Biosensor -- 26.4 Decentralized Deployment of Dense Network of Biosensors -- 26.5 Discussion and Extensions -- References. -- 27. Biochemical Transport Modeling, Estimation and Detection in Realistic Environments (Mathias Ortner and Arye Nehorai ) -- 27.1 Introduction -- 27.2 Physical and Statistical Models -- 27.3 Transport Modeling Using Monte Carlo Approximation -- 27.4 Localizing the Source(s) -- 27.5 Sequential Detection -- 27.6 Conclusion -- References -- 28. Security and Privacy for Sensor Networks (Wade Trappe, Peng Ning and Adrian Perrig) -- 28.1 Introduction -- 28.2 Security and Privacy Challenges -- 28.3 Ensuring Integrity of Measurement Process -- 28.4 Availability Attacks against the Wireless Link -- 28.5 Ensuring Privacy of Routing Contexts -- 28.6 Conclusion -- References -- Index.
Record Nr. UNINA-9911019320103321
Haykin Simon S. <1931->  
Hoboken, N.J., : John Wiley & Sons, 2009
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