{"product_id":"adaptive-filters-9781119979548","title":"Adaptive Filters","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis second edition of \u003ci\u003eAdaptive Filters: Theory and Applications\u003c\/i\u003e has been updated throughout to reflect the latest developments in this field; notably an increased coverage given to the practical applications of the theory to illustrate the much broader range of adaptive filters applications developed in recent years. The book offers an easy to understand approach to the theory and application of adaptive filters by clearly illustrating how the theory explained in the early chapters of the book is modified for the various applications discussed in detail in later chapters. This integrated approach makes the book a valuable resource for graduate students; and the inclusion of more advanced applications including antenna arrays and wireless communications makes it a suitable technical reference for engineers, practitioners and researchers.\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003e \u003cp\u003eKey features:\u003c\/p\u003e \u003cp\u003e Offers a thorough treatment of the theory of adaptive signal processing; incorporating new material on \u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003ePreface xvii\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eAcknowledgments xxi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Linear Filters 1\u003c\/p\u003e \u003cp\u003e1.2 Adaptive Filters 2\u003c\/p\u003e \u003cp\u003e1.3 Adaptive Filter Structures 3\u003c\/p\u003e \u003cp\u003e1.4 Adaptation Approaches 7\u003c\/p\u003e \u003cp\u003e1.5 Real and Complex Forms of Adaptive Filters 9\u003c\/p\u003e \u003cp\u003e1.6 Applications 9\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Discrete-Time Signals and Systems 28\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Sequences and z-Transform 28\u003c\/p\u003e \u003cp\u003e2.2 Parseval’s Relation 32\u003c\/p\u003e \u003cp\u003e2.3 System Function 33\u003c\/p\u003e \u003cp\u003e2.4 Stochastic Processes 35\u003c\/p\u003e \u003cp\u003eProblems 44\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Wiener Filters 48\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Mean-Squared Error Criterion 48\u003c\/p\u003e \u003cp\u003e3.2 Wiener Filter – Transversal, Real-Valued Case 50\u003c\/p\u003e \u003cp\u003e3.3 Principle of Orthogonality 55\u003c\/p\u003e \u003cp\u003e3.4 Normalized Performance Function 57\u003c\/p\u003e \u003cp\u003e3.5 Extension to Complex-Valued Case 58\u003c\/p\u003e \u003cp\u003e3.6 Unconstrained Wiener Filters 61\u003c\/p\u003e \u003cp\u003e3.7 Summary and Discussion 79\u003c\/p\u003e \u003cp\u003eProblems 80\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Eigenanalysis and Performance Surface 90\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Eigenvalues and Eigenvectors 90\u003c\/p\u003e \u003cp\u003e4.2 Properties of Eigenvalues and Eigenvectors 91\u003c\/p\u003e \u003cp\u003e4.3 Performance Surface 104\u003c\/p\u003e \u003cp\u003eProblems 112\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Search Methods 119\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Method of Steepest Descent 120\u003c\/p\u003e \u003cp\u003e5.2 Learning Curve 126\u003c\/p\u003e \u003cp\u003e5.3 Effect of Eigenvalue Spread 130\u003c\/p\u003e \u003cp\u003e5.4 Newton’s Method 131\u003c\/p\u003e \u003cp\u003e5.5 An Alternative Interpretation of Newton’s Algorithm 133\u003c\/p\u003e \u003cp\u003eProblems 135\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 LMS Algorithm 139\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Derivation of LMS Algorithm 139\u003c\/p\u003e \u003cp\u003e6.2 Average Tap-Weight Behavior of the LMS Algorithm 141\u003c\/p\u003e \u003cp\u003e6.3 MSE Behavior of the LMS Algorithm 144\u003c\/p\u003e \u003cp\u003e6.4 Computer Simulations 156\u003c\/p\u003e \u003cp\u003e6.5 Simplified LMS Algorithms 167\u003c\/p\u003e \u003cp\u003e6.6 Normalized LMS Algorithm 170\u003c\/p\u003e \u003cp\u003e6.7 Affine Projection LMS Algorithm 173\u003c\/p\u003e \u003cp\u003e6.8 Variable Step-Size LMS Algorithm 177\u003c\/p\u003e \u003cp\u003e6.9 LMS Algorithm for Complex-Valued Signals 179\u003c\/p\u003e \u003cp\u003e6.10 Beamforming (Revisited) 182\u003c\/p\u003e \u003cp\u003e6.11 Linearly Constrained LMS Algorithm 186\u003c\/p\u003e \u003cp\u003eProblems 190\u003c\/p\u003e \u003cp\u003eAppendix 6A: Derivation of Eq. (6.39) 205\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Transform Domain Adaptive Filters 207\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Overview of Transform Domain Adaptive Filters 208\u003c\/p\u003e \u003cp\u003e7.2 Band-Partitioning Property of Orthogonal Transforms 210\u003c\/p\u003e \u003cp\u003e7.3 Orthogonalization Property of Orthogonal Transforms 211\u003c\/p\u003e \u003cp\u003e7.4 Transform Domain LMS Algorithm 213\u003c\/p\u003e \u003cp\u003e7.5 Ideal LMS-Newton Algorithm and Its Relationship with TDLMS 215\u003c\/p\u003e \u003cp\u003e7.6 Selection of the Transform T 216\u003c\/p\u003e \u003cp\u003e7.7 Transforms 229\u003c\/p\u003e \u003cp\u003e7.8 Sliding Transforms 230\u003c\/p\u003e \u003cp\u003e7.9 Summary and Discussion 242\u003c\/p\u003e \u003cp\u003eProblems 243\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Block Implementation of Adaptive Filters 251\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Block LMS Algorithm 252\u003c\/p\u003e \u003cp\u003e8.2 Mathematical Background 255\u003c\/p\u003e \u003cp\u003e8.3 The FBLMS Algorithm 260\u003c\/p\u003e \u003cp\u003e8.4 The Partitioned FBLMS Algorithm 267\u003c\/p\u003e \u003cp\u003e8.5 Computer Simulations 276\u003c\/p\u003e \u003cp\u003eProblems 279\u003c\/p\u003e \u003cp\u003eAppendix 8A: Derivation of a Misadjustment Equation for the BLMS Algorithm 285\u003c\/p\u003e \u003cp\u003eAppendix 8B: Derivation of Misadjustment Equations for the FBLMS Algorithms 288\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Subband Adaptive Filters 294\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 DFT Filter Banks 295\u003c\/p\u003e \u003cp\u003e9.2 Complementary Filter Banks 299\u003c\/p\u003e \u003cp\u003e9.3 Subband Adaptive Filter Structures 303\u003c\/p\u003e \u003cp\u003e9.4 Selection of Analysis and Synthesis Filters 304\u003c\/p\u003e \u003cp\u003e9.5 Computational Complexity 307\u003c\/p\u003e \u003cp\u003e9.6 Decimation Factor and Aliasing 308\u003c\/p\u003e \u003cp\u003e9.7 Low-Delay Analysis and Synthesis Filter Banks 310\u003c\/p\u003e \u003cp\u003e9.8 A Design Procedure for Subband Adaptive Filters 313\u003c\/p\u003e \u003cp\u003e9.9 An Example 316\u003c\/p\u003e \u003cp\u003e9.10 Comparison with FBLMS Algorithm 318\u003c\/p\u003e \u003cp\u003eProblems 319\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 IIR Adaptive Filters 322\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Output Error Method 323\u003c\/p\u003e \u003cp\u003e10.2 Equation Error Method 327\u003c\/p\u003e \u003cp\u003e10.3 Case Study I: IIR Adaptive Line Enhancement 332\u003c\/p\u003e \u003cp\u003e10.4 Case Study II: Equalizer Design for Magnetic Recording Channels 343\u003c\/p\u003e \u003cp\u003e10.5 Concluding Remarks 349\u003c\/p\u003e \u003cp\u003eProblems 352\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Lattice Filters 355\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Forward Linear Prediction 355\u003c\/p\u003e \u003cp\u003e11.2 Backward Linear Prediction 357\u003c\/p\u003e \u003cp\u003e11.3 Relationship Between Forward and Backward Predictors 359\u003c\/p\u003e \u003cp\u003e11.4 Prediction-Error Filters 359\u003c\/p\u003e \u003cp\u003e11.5 Properties of Prediction Errors 360\u003c\/p\u003e \u003cp\u003e11.6 Derivation of Lattice Structure 362\u003c\/p\u003e \u003cp\u003e11.7 Lattice as an Orthogonalization Transform 367\u003c\/p\u003e \u003cp\u003e11.8 Lattice Joint Process Estimator 369\u003c\/p\u003e \u003cp\u003e11.9 System Functions 370\u003c\/p\u003e \u003cp\u003e11.10 Conversions 370\u003c\/p\u003e \u003cp\u003e11.11 All-Pole Lattice Structure 376\u003c\/p\u003e \u003cp\u003e11.12 Pole-Zero Lattice Structure 376\u003c\/p\u003e \u003cp\u003e11.13 Adaptive Lattice Filter 378\u003c\/p\u003e \u003cp\u003e11.14 Autoregressive Modeling of Random Processes 383\u003c\/p\u003e \u003cp\u003e11.15 Adaptive Algorithms Based on Autoregressive Modeling 385\u003c\/p\u003e \u003cp\u003eProblems 400\u003c\/p\u003e \u003cp\u003eAppendix 11A: Evaluation of E[ua(n)xT(n)K(n)x(n)uTa (n)] 407\u003c\/p\u003e \u003cp\u003eAppendix 11B: Evaluation of the parameter γ 408\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Method of Least-Squares 410\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Formulation of Least-Squares Estimation for a Linear Combiner 411\u003c\/p\u003e \u003cp\u003e12.2 Principle of Orthogonality 412\u003c\/p\u003e \u003cp\u003e12.3 Projection Operator 415\u003c\/p\u003e \u003cp\u003e12.4 Standard Recursive Least-Squares Algorithm 416\u003c\/p\u003e \u003cp\u003e12.5 Convergence Behavior of the RLS Algorithm 421\u003c\/p\u003e \u003cp\u003eProblems 430\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Fast RLS Algorithms 433\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Least-Squares Forward Prediction 434\u003c\/p\u003e \u003cp\u003e13.2 Least-Squares Backward Prediction 435\u003c\/p\u003e \u003cp\u003e13.3 Least-Squares Lattice 437\u003c\/p\u003e \u003cp\u003e13.4 RLSL Algorithm 440\u003c\/p\u003e \u003cp\u003e13.5 FTRLS Algorithm 453\u003c\/p\u003e \u003cp\u003eProblems 460\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Tracking 463\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Formulation of the Tracking Problem 463\u003c\/p\u003e \u003cp\u003e14.2 Generalized Formulation of LMS Algorithm 464\u003c\/p\u003e \u003cp\u003e14.3 MSE Analysis of the Generalized LMS Algorithm 465\u003c\/p\u003e \u003cp\u003e14.4 Optimum Step-Size Parameters 469\u003c\/p\u003e \u003cp\u003e14.5 Comparisons of Conventional Algorithms 471\u003c\/p\u003e \u003cp\u003e14.6 Comparisons Based on Optimum Step-Size Parameters 475\u003c\/p\u003e \u003cp\u003e14.7 VSLMS: An Algorithm with Optimum Tracking Behavior 477\u003c\/p\u003e \u003cp\u003e14.8 RLS Algorithm with Variable Forgetting Factor 485\u003c\/p\u003e \u003cp\u003e14.9 Summary 486\u003c\/p\u003e \u003cp\u003eProblems 488\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Echo Cancellation 492\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 The Problem Statement 492\u003c\/p\u003e \u003cp\u003e15.2 Structures and Adaptive Algorithms 495\u003c\/p\u003e \u003cp\u003e15.3 Double-Talk Detection 512\u003c\/p\u003e \u003cp\u003e15.4 Howling Suppression 521\u003c\/p\u003e \u003cp\u003e15.5 Stereophonic Acoustic Echo Cancellation 524\u003c\/p\u003e \u003cp\u003eAppendix 15A: Multitaper method 542\u003c\/p\u003e \u003cp\u003eAppendix 15B: Derivation of the Two-Channel Levinson–Durbin\u003c\/p\u003e \u003cp\u003eAlgorithm 549\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Active Noise Control 551\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Broadband Feedforward Single-Channel ANC 553\u003c\/p\u003e \u003cp\u003e16.2 Narrowband Feedforward Single-Channel ANC 559\u003c\/p\u003e \u003cp\u003e16.3 Feedback Single-Channel ANC 573\u003c\/p\u003e \u003cp\u003e16.4 Multichannel ANC Systems 577\u003c\/p\u003e \u003cp\u003eAppendix 16A: Derivation of Eq. (16.46) 582\u003c\/p\u003e \u003cp\u003eAppendix 16B: Derivation of Eq. (16.53) 583\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Synchronization and Equalization in Data Transmission Systems 584\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 Continuous Time Channel Model 585\u003c\/p\u003e \u003cp\u003e17.2 Discrete Time Channel Model and Equalizer Structures 589\u003c\/p\u003e \u003cp\u003e17.3 Timing Recovery 593\u003c\/p\u003e \u003cp\u003e17.4 Equalizers Design and Performance Analysis 606\u003c\/p\u003e \u003cp\u003e17.5 Adaptation Algorithms 617\u003c\/p\u003e \u003cp\u003e17.6 Cyclic Equalization 618\u003c\/p\u003e \u003cp\u003e17.7 Joint Timing Recovery, Carrier Recovery, and Channel Equalization 628\u003c\/p\u003e \u003cp\u003e17.8 Maximum Likelihood Detection 629\u003c\/p\u003e \u003cp\u003e17.9 Soft Equalization 631\u003c\/p\u003e \u003cp\u003e\u003cbr\u003e 17.10 Single-Input Multiple-Output Equalization 643\u003c\/p\u003e \u003cp\u003e17.11 Frequency Domain Equalization 645\u003c\/p\u003e \u003cp\u003e17.12 Blind Equalization 649\u003c\/p\u003e \u003cp\u003eProblems 654\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Sensor Array Processing 659\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Narrowband Sensor Arrays 660\u003c\/p\u003e \u003cp\u003e18.2 Broadband Sensor Arrays 678\u003c\/p\u003e \u003cp\u003e18.3 Robust Beamforming 683\u003c\/p\u003e \u003cp\u003eProblems 692\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Code Division Multiple Access Systems 695\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 CDMA Signal Model 695\u003c\/p\u003e \u003cp\u003e19.2 Linear Detectors 699\u003c\/p\u003e \u003cp\u003e19.3 Adaptation Methods 707\u003c\/p\u003e \u003cp\u003eProblems 709\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 OFDM and MIMO Communications 711\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e20.1 OFDM Communication Systems 711\u003c\/p\u003e \u003cp\u003e20.2 MIMO Communication Systems 730\u003c\/p\u003e \u003cp\u003e20.3 MIMO–OFDM 743\u003c\/p\u003e \u003cp\u003e\u003ci\u003eProblems 743\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eReferences 746\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eIndex 761\u003c\/i\u003e\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407198593367,"sku":"9781119979548","price":92.1,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119979548.jpg?v=1730498534","url":"https:\/\/bookcurl.com\/products\/adaptive-filters-9781119979548","provider":"Book Curl","version":"1.0","type":"link"}