05625nam 2200673 450 99620378860331620230829172724.01-282-65650-397866126565070-470-57575-10-470-57574-310.1002/9780470575758(CKB)2670000000032876(EBL)554990(SSID)ssj0000402484(PQKBManifestationID)11276171(PQKBTitleCode)TC0000402484(PQKBWorkID)10426814(PQKB)10259682(MiAaPQ)EBC554990(CaBNVSL)mat05521814(IDAMS)0b000064812d17b5(IEEE)5521814(PPN)176131914(CaSebORM)9780470195178(OCoLC)644162805(EXLCZ)99267000000003287620151221d2010 uy engur|n|---|||||txtccrAdaptive signal processing next generation solutions /edited by Tèulay Adali, Simon Haykin1st editionNew York :IEEE, Institute of Electrical and Electronics Engineers,c2010.[Piscataqay, New Jersey] :IEEE Xplore,[2010]1 online resource (428 p.)Adaptive and learning systems for signal processing, communications and control series ;55Description based upon print version of record.0-470-19517-7 Includes bibliographical references and index.Preface -- Contributors -- Chapter 1 Complex-Valued Adaptive Signal Processing -- 1.1 Introduction -- -- 1.2 Preliminaries -- 1.3 Optimization in the Complex Domain -- 1.4 Widely Linear Adaptive Filtering -- 1.5 Nonlinear Adaptive Filtering with Multilayer Perceptrons -- 1.6 Complex Independent Component Analysis -- 1.7 Summary -- 1.8 Acknowledgment -- 1.9 Problems -- References -- Chapter 2 Robust Estimation Techniques for Complex-Valued Random Vectors -- 2.1 Introduction -- 2.2 Statistical Characterization of Complex Random Vectors -- 2.3 Complex Elliptically Symmetric (CES) Distributions -- 2.4 Tools to Compare Estimators -- 2.5 Scatter and Pseudo-Scatter Matrices -- 2.6 Array Processing Examples -- 2.7 MVDR Beamformers Based on M-Estimators -- 2.8 Robust ICA -- 2.9 Conclusion -- 2.10 Problems -- References -- Chapter 3 Turbo Equalization -- 3.1 Introduction -- 3.2 Context -- 3.3 Communication Chain -- 3.4 Turbo Decoder: Overview -- 3.5 Forward-Backward Algorithm -- 3.6 Simplified Algorithm: Interference Canceler -- 3.7 Capacity Analysis -- 3.8 Blind Turbo Equalization -- 3.9 Convergence -- 3.10 Multichannel and Multiuser Settings -- 3.11 Concluding Remarks -- 3.12 Problems -- References -- Chapter 4 Subspace Tracking for Signal Processing -- 4.1 Introduction -- 4.2 Linear Algebra Review -- 4.3 Observation Model and Problem Statement -- 4.4 Preliminary Example: Oja's Neuron -- 4.5 Subspace Tracking -- 4.6 Eigenvectors Tracking -- 4.7 Convergence and Performance Analysis Issues -- 4.8 Illustrative Examples -- 4.9 Concluding Remarks -- 4.10 Problems -- References -- Chapter 5 Particle Filtering -- 5.1 Introduction -- 5.2 Motivation for Use of Particle Filtering -- 5.3 The Basic Idea -- 5.4 The Choice of Proposal Distribution and Resampling -- 5.5 Some Particle Filtering Methods -- 5.6 Handling Constant Parameters -- 5.7 Rao-Blackwellization -- 5.8 Prediction -- 5.9 Smoothing -- 5.10 Convergence Issues -- 5.11 Computational Issues and Hardware Implementation -- 5.12 Acknowledgments.5.13 Exercises -- References -- Chapter 6 Nonlinear Sequential State Estimation for Solving Pattern-Classification Problems -- 6.1 Introduction -- 6.2 Back-Propagation and Support Vector Machine-Learning Algorithms: Review -- 6.3 Supervised Training Framework of MLPs Using Nonlinear Sequential State Estimation -- 6.4 The Extended Kalman Filter -- 6.5 Experimental Comparison of the Extended Kalman Filtering Algorithm with the Back-Propagation and Support Vector Machine Learning Algorithms -- 6.6 Concluding Remarks -- 6.7 Problems -- References -- Chapter 7 Bandwidth Extension of Telephony Speech -- 7.1 Introduction -- 7.2 Organization of the Chapter -- 7.3 Nonmodel-Based Algorithms for Bandwidth Extension -- 7.4 Basics -- 7.5 Model-Based Algorithms for Bandwidth Extension -- 7.6 Evaluation of Bandwidth Extension Algorithms -- 7.7 Conclusion -- 7.8 Problems -- References -- Index.Leading experts present the latest research results in adaptive signal processing Recent developments in signal processing have made it clear that significant performance gains can be achieved beyond those achievable using standard adaptive filtering approaches. Adaptive Signal Processing presents the next generation of algorithms that will produce these desired results, with an emphasis on important applications and theoretical advancements. This highly unique resource brings together leading authorities in the field writing on the key topics of significance, each at the cuttiAdaptive and learning systems for signal processing, communications, and control ;55Adaptive signal processingAdaptive signal processing.621.382/2621.3822Adali Tülay845678Haykin Simon S.1931-8857CaBNVSLCaBNVSLCaBNVSLBOOK996203788603316Adaptive signal processing1887893UNISA03249nam 2200625 a 450 991083000540332120170810193451.01-118-04446-01-283-07255-697866130725591-118-38683-31-118-04444-4(CKB)2550000000032194(EBL)700436(OCoLC)726828586(SSID)ssj0000539596(PQKBManifestationID)11362287(PQKBTitleCode)TC0000539596(PQKBWorkID)10579848(PQKB)10653460(MiAaPQ)EBC700436(PPN)165101415(EXLCZ)99255000000003219420101220d2011 uy 0engur|n|---|||||txtccrThe nonprofit outcomes toolbox[electronic resource] a complete guide to program effectiveness, performance measurement, and results /Robert M. Penna ; foreword by Ken BergerHoboken, N.J. John Wiley & Sonsc20111 online resource (380 p.)Wiley nonprofit authority ;1Includes index.1-118-00450-7 pt. 1. The basics -- pt. 2. Working with outcomes -- pt. 3. Advanced tools -- pt. 4. Other tools and perspectives."An invaluable guide to the outcome-based tools needed to help nonprofit organizations increase their effectiveness The Nonprofit Outcomes Toolbox identifies stages in the use of outcomes and shows you how to use specific facets of existing outcome models to improve performance and achieve meaningful results. Going beyond the familiar limits of the sector, this volume also illustrates how tools and approaches long in use in the corporate sector can be of great analytical and practical use to nonprofit, philanthropic, and governmental organizations. An outstanding resource for organizational and program leaders interested in improving performance, there is nothing else like this work currently available. Shows how to identify and set meaningful, sustainable outcomes. Illustrates how to track and manage with outcomes. Offers guidance in assessing capacity, and using outcome-based communications. Features a companion Web site with the tools found in this book. Providing the tools and explanations needed to achieve program success, this book is a complete resource for the nonprofit, governmental, or philanthropic professional striving for greater effectiveness in programs or organizations"--Provided by publisher.Wiley Nonprofit AuthorityNonprofit organizationsManagementEvaluationSocial serviceEvaluationNonprofit organizationsManagementEvaluation.Social serviceEvaluation.658.048658/.048BUS074000bisacshPenna Robert Mark1612227Rensselaerville Institute.Charity Navigator (Firm)MiAaPQMiAaPQMiAaPQBOOK9910830005403321The nonprofit outcomes toolbox3940904UNINA