Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Kalman filtering : theory and practice using MATLAB / Mohinder S. Grewal, Angus P. Andrews
| Kalman filtering : theory and practice using MATLAB / Mohinder S. Grewal, Angus P. Andrews |
| Autore | Grewal, Mohinder S. |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J. : Wiley, c2008 |
| Descrizione fisica | xvi, 575 p. : ill. ; 25 cm. + 1 CD-ROM |
| Disciplina | 629.8312 |
| Altri autori (Persone) | Andrews, Angus P. |
| Soggetto topico | Kalman filtering |
| ISBN | 9780470173664 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991002096829707536 |
Grewal, Mohinder S.
|
||
| Hoboken, N.J. : Wiley, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
| ||
Kalman filtering : theory and practice using MATLAB / Mohinder S. Grewal, Angus P. Andrews
| Kalman filtering : theory and practice using MATLAB / Mohinder S. Grewal, Angus P. Andrews |
| Autore | Grewal, Mohinder S. |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | New York : Wiley, 2001 |
| Descrizione fisica | xiii, 401 p. : ill. ; 25 cm. + 1 cd |
| Disciplina | 003.5 |
| Altri autori (Persone) | Andrews, Angus P. |
| Soggetto topico | Kalman filtering |
| ISBN | 0471392545 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991001660289707536 |
|
Grewal, Mohinder S.
|
||
| New York : Wiley, 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
| ||
Kalman filtering and neural networks [[electronic resource] /] / edited by Simon Haykin
| Kalman filtering and neural networks [[electronic resource] /] / edited by Simon Haykin |
| Pubbl/distr/stampa | New York, : Wiley, c2001 |
| Descrizione fisica | 1 online resource (302 p.) |
| Disciplina |
006.3/2
621.3815324 |
| Altri autori (Persone) | HaykinSimon S. <1931-> |
| Collana | Adaptive and learning systems for signal processing, communications, and control |
| Soggetto topico |
Kalman filtering
Neural networks (Computer science) |
| ISBN |
1-280-36756-3
9786610367566 0-470-31226-2 0-471-46421-X 0-471-22154-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
KALMAN FILTERING AND NEURAL NETWORKS; CONTENTS; Preface; Contributors; 1 Kalman Filters; 1.1 Introduction; 1.2 Optimum Estimates; 1.3 Kalman Filter; 1.4 Divergence Phenomenon: Square-Root Filtering; 1.5 Rauch-Tung-Striebel Smoother; 1.6 Extended Kalman Filter; 1.7 Summary; References; 2 Parameter-Based Kalman Filter Training: Theory and Implementation; 2.1 Introduction; 2.2 Network Architectures; 2.3 The EKF Procedure; 2.3.1 Global EKF Training; 2.3.2 Learning Rate and Scaled Cost Function; 2.3.3 Parameter Settings; 2.4 Decoupled EKF (DEKF); 2.5 Multistream Training
2.5.1 Some Insight into the Multistream Technique2.5.2 Advantages and Extensions of Multistream Training; 2.6 Computational Considerations; 2.6.1 Derivative Calculations; 2.6.2 Computationally Efficient Formulations for Multiple-Output Problems; 2.6.3 Avoiding Matrix Inversions; 2.6.4 Square-Root Filtering; 2.7 Other Extensions and Enhancements; 2.7.1 EKF Training with Constrained Weights; 2.7.2 EKF Training with an Entropic Cost Function; 2.7.3 EKF Training with Scalar Errors; 2.8 Automotive Applications of EKF Training; 2.8.1 Air/Fuel Ratio Control; 2.8.2 Idle Speed Control 2.8.3 Sensor-Catalyst Modeling2.8.4 Engine Misfire Detection; 2.8.5 Vehicle Emissions Estimation; 2.9 Discussion; 2.9.1 Virtues of EKF Training; 2.9.2 Limitations of EKF Training; 2.9.3 Guidelines for Implementation and Use; References; 3 Learning Shape and Motion from Image Sequences; 3.1 Introduction; 3.2 Neurobiological and Perceptual Foundations of our Model; 3.3 Network Description; 3.4 Experiment 1; 3.5 Experiment 2; 3.6 Experiment 3; 3.7 Discussion; References; 4 Chaotic Dynamics; 4.1 Introduction; 4.2 Chaotic (Dynamic) Invariants; 4.3 Dynamic Reconstruction 4.4 Modeling Numerically Generated Chaotic Time Series4.4.1 Logistic Map; 4.4.2 Ikeda Map; 4.4.3 Lorenz Attractor; 4.5 Nonlinear Dynamic Modeling of Real-World Time Series; 4.5.1 Laser Intensity Pulsations; 4.5.2 Sea Clutter Data; 4.6 Discussion; References; 5 Dual Extended Kalman Filter Methods; 5.1 Introduction; 5.2 Dual EKF-Prediction Error; 5.2.1 EKF-State Estimation; 5.2.2 EKF-Weight Estimation; 5.2.3 Dual Estimation; 5.3 A Probabilistic Perspective; 5.3.1 Joint Estimation Methods; 5.3.2 Marginal Estimation Methods; 5.3.3 Dual EKF Algorithms; 5.3.4 Joint EKF 5.4 Dual EKF Variance Estimation5.5 Applications; 5.5.1 Noisy Time-Series Estimation and Prediction; 5.5.2 Economic Forecasting-Index of Industrial Production; 5.5.3 Speech Enhancement; 5.6 Conclusions; Acknowledgments; Appendix A: Recurrent Derivative of the Kalman Gain; Appendix B: Dual EKF with Colored Measurement Noise; References; 6 Learning Nonlinear Dynamical System Using the Expectation-Maximization Algorithm; 6.1 Learning Stochastic Nonlinear Dynamics; 6.1.1 State Inference and Model Learning; 6.1.2 The Kalman Filter; 6.1.3 The EM Algorithm; 6.2 Combining EKS and EM 6.2.1 Extended Kalman Smoothing (E-step) |
| Record Nr. | UNINA-9910830752003321 |
| New York, : Wiley, c2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Kalman filtering and neural networks [[electronic resource] /] / edited by Simon Haykin
| Kalman filtering and neural networks [[electronic resource] /] / edited by Simon Haykin |
| Pubbl/distr/stampa | New York, : Wiley, c2001 |
| Descrizione fisica | 1 online resource (302 p.) |
| Disciplina |
006.3/2
621.3815324 |
| Altri autori (Persone) | HaykinSimon S. <1931-> |
| Collana | Adaptive and learning systems for signal processing, communications, and control |
| Soggetto topico |
Kalman filtering
Neural networks (Computer science) |
| ISBN |
1-280-36756-3
9786610367566 0-470-31226-2 0-471-46421-X 0-471-22154-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
KALMAN FILTERING AND NEURAL NETWORKS; CONTENTS; Preface; Contributors; 1 Kalman Filters; 1.1 Introduction; 1.2 Optimum Estimates; 1.3 Kalman Filter; 1.4 Divergence Phenomenon: Square-Root Filtering; 1.5 Rauch-Tung-Striebel Smoother; 1.6 Extended Kalman Filter; 1.7 Summary; References; 2 Parameter-Based Kalman Filter Training: Theory and Implementation; 2.1 Introduction; 2.2 Network Architectures; 2.3 The EKF Procedure; 2.3.1 Global EKF Training; 2.3.2 Learning Rate and Scaled Cost Function; 2.3.3 Parameter Settings; 2.4 Decoupled EKF (DEKF); 2.5 Multistream Training
2.5.1 Some Insight into the Multistream Technique2.5.2 Advantages and Extensions of Multistream Training; 2.6 Computational Considerations; 2.6.1 Derivative Calculations; 2.6.2 Computationally Efficient Formulations for Multiple-Output Problems; 2.6.3 Avoiding Matrix Inversions; 2.6.4 Square-Root Filtering; 2.7 Other Extensions and Enhancements; 2.7.1 EKF Training with Constrained Weights; 2.7.2 EKF Training with an Entropic Cost Function; 2.7.3 EKF Training with Scalar Errors; 2.8 Automotive Applications of EKF Training; 2.8.1 Air/Fuel Ratio Control; 2.8.2 Idle Speed Control 2.8.3 Sensor-Catalyst Modeling2.8.4 Engine Misfire Detection; 2.8.5 Vehicle Emissions Estimation; 2.9 Discussion; 2.9.1 Virtues of EKF Training; 2.9.2 Limitations of EKF Training; 2.9.3 Guidelines for Implementation and Use; References; 3 Learning Shape and Motion from Image Sequences; 3.1 Introduction; 3.2 Neurobiological and Perceptual Foundations of our Model; 3.3 Network Description; 3.4 Experiment 1; 3.5 Experiment 2; 3.6 Experiment 3; 3.7 Discussion; References; 4 Chaotic Dynamics; 4.1 Introduction; 4.2 Chaotic (Dynamic) Invariants; 4.3 Dynamic Reconstruction 4.4 Modeling Numerically Generated Chaotic Time Series4.4.1 Logistic Map; 4.4.2 Ikeda Map; 4.4.3 Lorenz Attractor; 4.5 Nonlinear Dynamic Modeling of Real-World Time Series; 4.5.1 Laser Intensity Pulsations; 4.5.2 Sea Clutter Data; 4.6 Discussion; References; 5 Dual Extended Kalman Filter Methods; 5.1 Introduction; 5.2 Dual EKF-Prediction Error; 5.2.1 EKF-State Estimation; 5.2.2 EKF-Weight Estimation; 5.2.3 Dual Estimation; 5.3 A Probabilistic Perspective; 5.3.1 Joint Estimation Methods; 5.3.2 Marginal Estimation Methods; 5.3.3 Dual EKF Algorithms; 5.3.4 Joint EKF 5.4 Dual EKF Variance Estimation5.5 Applications; 5.5.1 Noisy Time-Series Estimation and Prediction; 5.5.2 Economic Forecasting-Index of Industrial Production; 5.5.3 Speech Enhancement; 5.6 Conclusions; Acknowledgments; Appendix A: Recurrent Derivative of the Kalman Gain; Appendix B: Dual EKF with Colored Measurement Noise; References; 6 Learning Nonlinear Dynamical System Using the Expectation-Maximization Algorithm; 6.1 Learning Stochastic Nonlinear Dynamics; 6.1.1 State Inference and Model Learning; 6.1.2 The Kalman Filter; 6.1.3 The EM Algorithm; 6.2 Combining EKS and EM 6.2.1 Extended Kalman Smoothing (E-step) |
| Record Nr. | UNINA-9910841275303321 |
| New York, : Wiley, c2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Kalman Filters : Theory for Advanced Applications / / edited by Ginalber Luiz Serra
| Kalman Filters : Theory for Advanced Applications / / edited by Ginalber Luiz Serra |
| Pubbl/distr/stampa | Rijeka, Croatia : , : IntechOpen, , 2018 |
| Descrizione fisica | 1 online resource (314 pages) : illustrations some color |
| Disciplina | 629.8312 |
| Soggetto topico | Kalman filtering |
| ISBN |
953-51-4038-8
953-51-3828-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Kalman filters |
| Record Nr. | UNINA-9910317832703321 |
| Rijeka, Croatia : , : IntechOpen, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Measure theory and filtering : introduction and applications / Lakhdar Aggoun, Robert J. Elliott
| Measure theory and filtering : introduction and applications / Lakhdar Aggoun, Robert J. Elliott |
| Autore | Aggoun, Lakhdar |
| Pubbl/distr/stampa | Cambridge : Cambridge University Press, 2004 |
| Descrizione fisica | x, 258 p. 26 cm |
| Disciplina | 515.42 |
| Altri autori (Persone) | Elliott, Robert Jamesauthor |
| Collana | Cambridge series on statistical and probabilistic mathematics |
| Soggetto topico |
Measure theory
Kalman filtering |
| ISBN | 0521838037 |
| Classificazione |
AMS 60-02
LC QA312.A34 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991000895379707536 |
|
Aggoun, Lakhdar
|
||
| Cambridge : Cambridge University Press, 2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
| ||
Multi-purpose acoustic target tracking for additive situational awareness [[electronic resource] /] / Latasha Solomon
| Multi-purpose acoustic target tracking for additive situational awareness [[electronic resource] /] / Latasha Solomon |
| Autore | Solomon Latasha |
| Pubbl/distr/stampa | Adelphi, MD : , : Army Research Laboratory, , [2008] |
| Descrizione fisica | vi, 12 pages : digital, PDF file |
| Collana | ARL-TR |
| Soggetto topico |
Target acquisition
Sound-waves Kalman filtering Acoustic localization |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910698037903321 |
|
Solomon Latasha
|
||
| Adelphi, MD : , : Army Research Laboratory, , [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Optimal state estimation [[electronic resource] ] : Kalman, H [infinity] and nonlinear approaches / / Dan Simon
| Optimal state estimation [[electronic resource] ] : Kalman, H [infinity] and nonlinear approaches / / Dan Simon |
| Autore | Simon Dan <1960-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (554 p.) |
| Disciplina |
519
629.8312 |
| Soggetto topico |
Kalman filtering
Nonlinear systems Mathematical optimization |
| ISBN |
1-280-50795-0
9786610507955 0-470-04534-5 1-61583-476-1 0-470-04533-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Optimal State Estimation; CONTENTS; Acknowledgments; Acronyms; List of algorithms; Introduction; PART I INTRODUCTORY MATERIAL; 1 Linear systems theory; 1.1 Matrix algebra and matrix calculus; 1.1.1 Matrix algebra; 1.1.2 The matrix inversion lemma; 1.1.3 Matrix calculus; 1.1.4 The history of matrices; 1.2 Linear systems; 1.3 Nonlinear systems; 1.4 Discretization; 1.5 Simulation; 1.5.1 Rectangular integration; 1.5.2 Trapezoidal integration; 1.5.3 Runge-Kutta integration; 1.6 Stability; 1.6.1 Continuous-time systems; 1.6.2 Discrete-time systems; 1.7 Controllability and observability
1.7.1 Controllability1.7.2 Observability; 1.7.3 Stabilizability and detectability; 1.8 Summary; Problems; 2 Probability theory; 2.1 Probability; 2.2 Random variables; 2.3 Transformations of random variables; 2.4 Multiple random variables; 2.4.1 Statistical independence; 2.4.2 Multivariate statistics; 2.5 Stochastic Processes; 2.6 White noise and colored noise; 2.7 Simulating correlated noise; 2.8 Summary; Problems; 3 Least squares estimation; 3.1 Estimation of a constant; 3.2 Weighted least squares estimation; 3.3 Recursive least squares estimation; 3.3.1 Alternate estimator forms 3.3.2 Curve fitting3.4 Wiener filtering; 3.4.1 Parametric filter optimization; 3.4.2 General filter optimization; 3.4.3 Noncausal filter optimization; 3.4.4 Causal filter optimization; 3.4.5 Comparison; 3.5 Summary; Problems; 4 Propagation of states and covariances; 4.1 Discrete-time systems; 4.2 Sampled-data systems; 4.3 Continuous-time systems; 4.4 Summary; Problems; PART II THE KALMAN FILTER; 5 The discrete-time Kalman filter; 5.1 Derivation of the discrete-time Kalman filter; 5.2 Kalman filter properties; 5.3 One-step Kalman filter equations; 5.4 Alternate propagation of covariance 5.4.1 Multiple state systems5.4.2 Scalar systems; 5.5 Divergence issues; 5.6 Summary; Problems; 6 Alternate Kalman filter formulations; 6.1 Sequential Kalman filtering; 6.2 Information filtering; 6.3 Square root filtering; 6.3.1 Condition number; 6.3.2 The square root time-update equation; 6.3.3 Potter's square root measurement-update equation; 6.3.4 Square root measurement update via triangularization; 6.3.5 Algorithms for orthogonal transformations; 6.4 U-D filtering; 6.4.1 U-D filtering: The measurement-update equation; 6.4.2 U-D filtering: The time-update equation; 6.5 Summary; Problems 7 Kalman filter generalizations7.1 Correlated process and measurement noise; 7.2 Colored process and measurement noise; 7.2.1 Colored process noise; 7.2.2 Colored measurement noise: State augmentation; 7.2.3 Colored measurement noise: Measurement differencing; 7.3 Steady-state filtering; 7.3.1 α-β filtering; 7.3.2 α-β-γ filtering; 7.3.3 A Hamiltonian approach to steady-state filtering; 7.4 Kalman filtering with fading memory; 7.5 Constrained Kalman filtering; 7.5.1 Model reduction; 7.5.2 Perfect measurements; 7.5.3 Projection approaches; 7.5.4 A pdf truncation approach; 7.6 Summary; Problems 8 The continuous-time Kalman filter |
| Record Nr. | UNINA-9910143568103321 |
|
Simon Dan <1960->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Optimal state estimation : Kalman, H [infinity] and nonlinear approaches / / Dan Simon
| Optimal state estimation : Kalman, H [infinity] and nonlinear approaches / / Dan Simon |
| Autore | Simon Dan <1960-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (554 p.) |
| Disciplina |
519
629.8312 |
| Soggetto topico |
Kalman filtering
Nonlinear systems Mathematical optimization |
| ISBN |
1-280-50795-0
9786610507955 0-470-04534-5 1-61583-476-1 0-470-04533-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Optimal State Estimation; CONTENTS; Acknowledgments; Acronyms; List of algorithms; Introduction; PART I INTRODUCTORY MATERIAL; 1 Linear systems theory; 1.1 Matrix algebra and matrix calculus; 1.1.1 Matrix algebra; 1.1.2 The matrix inversion lemma; 1.1.3 Matrix calculus; 1.1.4 The history of matrices; 1.2 Linear systems; 1.3 Nonlinear systems; 1.4 Discretization; 1.5 Simulation; 1.5.1 Rectangular integration; 1.5.2 Trapezoidal integration; 1.5.3 Runge-Kutta integration; 1.6 Stability; 1.6.1 Continuous-time systems; 1.6.2 Discrete-time systems; 1.7 Controllability and observability
1.7.1 Controllability1.7.2 Observability; 1.7.3 Stabilizability and detectability; 1.8 Summary; Problems; 2 Probability theory; 2.1 Probability; 2.2 Random variables; 2.3 Transformations of random variables; 2.4 Multiple random variables; 2.4.1 Statistical independence; 2.4.2 Multivariate statistics; 2.5 Stochastic Processes; 2.6 White noise and colored noise; 2.7 Simulating correlated noise; 2.8 Summary; Problems; 3 Least squares estimation; 3.1 Estimation of a constant; 3.2 Weighted least squares estimation; 3.3 Recursive least squares estimation; 3.3.1 Alternate estimator forms 3.3.2 Curve fitting3.4 Wiener filtering; 3.4.1 Parametric filter optimization; 3.4.2 General filter optimization; 3.4.3 Noncausal filter optimization; 3.4.4 Causal filter optimization; 3.4.5 Comparison; 3.5 Summary; Problems; 4 Propagation of states and covariances; 4.1 Discrete-time systems; 4.2 Sampled-data systems; 4.3 Continuous-time systems; 4.4 Summary; Problems; PART II THE KALMAN FILTER; 5 The discrete-time Kalman filter; 5.1 Derivation of the discrete-time Kalman filter; 5.2 Kalman filter properties; 5.3 One-step Kalman filter equations; 5.4 Alternate propagation of covariance 5.4.1 Multiple state systems5.4.2 Scalar systems; 5.5 Divergence issues; 5.6 Summary; Problems; 6 Alternate Kalman filter formulations; 6.1 Sequential Kalman filtering; 6.2 Information filtering; 6.3 Square root filtering; 6.3.1 Condition number; 6.3.2 The square root time-update equation; 6.3.3 Potter's square root measurement-update equation; 6.3.4 Square root measurement update via triangularization; 6.3.5 Algorithms for orthogonal transformations; 6.4 U-D filtering; 6.4.1 U-D filtering: The measurement-update equation; 6.4.2 U-D filtering: The time-update equation; 6.5 Summary; Problems 7 Kalman filter generalizations7.1 Correlated process and measurement noise; 7.2 Colored process and measurement noise; 7.2.1 Colored process noise; 7.2.2 Colored measurement noise: State augmentation; 7.2.3 Colored measurement noise: Measurement differencing; 7.3 Steady-state filtering; 7.3.1 α-β filtering; 7.3.2 α-β-γ filtering; 7.3.3 A Hamiltonian approach to steady-state filtering; 7.4 Kalman filtering with fading memory; 7.5 Constrained Kalman filtering; 7.5.1 Model reduction; 7.5.2 Perfect measurements; 7.5.3 Projection approaches; 7.5.4 A pdf truncation approach; 7.6 Summary; Problems 8 The continuous-time Kalman filter |
| Record Nr. | UNINA-9910678143103321 |
|
Simon Dan <1960->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sigma-Punkt Kalman-Filter Mit Ungleichungsnebenbedingungen / / Paul Schneider
| Sigma-Punkt Kalman-Filter Mit Ungleichungsnebenbedingungen / / Paul Schneider |
| Autore | Schneider Paul |
| Pubbl/distr/stampa | Berlin : , : Logos-Verl, , 2011 |
| Descrizione fisica | 1 online resource (xii, 158 pages) |
| Disciplina | 629.8312 |
| Soggetto topico | Kalman filtering |
| Soggetto genere / forma | Electronic books. |
| ISBN | 3-8325-9807-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ger |
| Record Nr. | UNINA-9910467080503321 |
|
Schneider Paul
|
||
| Berlin : , : Logos-Verl, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
