MARC Record from marc_columbia

LEADER: 09348cam a2200817Ma 4500
001 14747723
005 20220501001956.0
006 m o d
007 cr |n|||||||||
008 940719s1995 nyua ob 001 0 eng d
035 $a(OCoLC)on1066690871
035 $a(NNC)14747723
040 $aWYU$beng$cWYU$dOCLCO$dYDX$dOCLCF$dOCLCQ$dAU@$dZCU$dSFB$dUKAHL$dOCLCO
015 $aGBB8F6626$2bnb
019 $a1033786064$a1097102825$a1140431850$a1260355716
020 $a9781351468947
020 $a1351468944
020 $z0824792890$q(acid-free paper)
020 $z9780824792893
020 $z0824774922
020 $z9780824774929
020 $a9781315136653$q(electronic bk.)
020 $a1315136651$q(electronic bk.)
024 7 $a10.1201/9781315136653$2doi
035 $a(OCoLC)1066690871$z(OCoLC)1033786064$z(OCoLC)1097102825$z(OCoLC)1140431850$z(OCoLC)1260355716
037 $a9781351468947$bIngram Content Group
050 14 $aTK5102.9$b.R44 1995
082 04 $a621.382/2$220
084 $a53.70$2bcl
084 $aELT 479f$2stub
084 $aELT 484f$2stub
084 $aELT 515f$2stub
084 $aSK 880$2rvk
084 $aZN 5700$2rvk
049 $aZCUA
100 1 $aRegalia, Phillip A.,$d1962-
240 10 $aAdaptive IIR filtering in signal processing and control (Online)
245 10 $aAdaptive IIR filtering in signal processing and control /$cPhillip A. Regalia.
260 $aNew York :$bM. Dekker,$c©1995.
300 $a1 online resource (xvii, 678 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aElectrical engineering and electronics ;$v90
504 $aIncludes bibliographical references and index.
505 0 $aCover -- Half Title -- Title Page -- Copyrigth Page -- Dedication -- Preface -- Table of Contents -- 1: Introduction -- 1.1 Overview -- 1.2 Central Problem Statement -- 1.3 A Brief Glimpse into Approximation Criteria -- 1.4 Some Notations -- 1.5 Of Things not Belabored -- 1.5.1 Persistent Excitation -- 1.5.2 Parametrizations and Variances -- 1.5.3 Equation Error versus Output Error -- References -- 2: Recursive Filter Structures -- 2.1 Review of Linear System Theory -- 2.1.1 Controllability and Observability Grammians -- 2.1.2 Minimality and Parametrization -- 2.1.3 Balanced Forms and Hankel Singular Values -- 2.2 Direct Form Filters -- 2.3 Parallel and Cascade Forms -- 2.4 Tapped State Lattice Form -- 2.4.1 A Lattice Filter Primer -- 2.4.2 Schur Recursions -- 2.4.3 Bounded Real Lemma -- 2.4.4 Szegö Polynomials and Orthonormal Basis Functions -- 2.4.5 Relations with Direct Form Filter -- Problems -- References -- 3: The Beurling-Lax Theorem, Hankel Forms, and Classical Identification -- 3.1 The Bcurling-Lax Theorem -- 3.1.1 Shift-Invariant Subspaces -- 3.1.2 Orthogonal Filters and All-Pass Completions -- 3.1.3 Second Proof -- 3.2 Hankel Forms -- 3.3 Padé Approximations (Prony's Method) -- 3.4 Equation Error Methods -- 3.4.1 Sufficient-Order Case -- 3.4.2 Undermodelled Case -- 3.5 Output Error Methods -- 3.6 Recapitulation -- Problems -- References -- 4: Rational Approximation in Hankel Norm -- 4.1 Problem Statement -- 4.2 Schmidt Form or SVD -- 4.3 The Hankel Norm -- 4.4 Nehari's Theorem -- 4.5 Constructing the Hankel Norm Approximant -- 4.6 Repeated Hankel Singular Values -- 4.7 Some Bounds for Other Criteria -- Problems -- References -- 5: Rational H2 Approximation -- 5.1 Normality of the Rational H2 Approximation Problem -- 5.2 The Reduced Error Surface -- 5.3 Invariance to Frequency Transformations -- 5.4 Index of Stationary Points.
505 8 $a5.5 Relations to the Hankel Norm Problem -- Problems -- References -- 6: Stability of Time-Varying Recursive Filters -- 6.1 Time-Varying Recursive Filters -- 6.2 BIBO and Exponential Stability -- 6.3 Slow Variation Analyses -- 6.4 Lyapunov Methods -- Problems -- References -- 7: Gradient Descent Algorithms -- 7.1 The Mean-Square Cost Function -- 7.2 Direct Form Algorithm -- 7.3 An Introduction to the ODE Method -- 7.3.1 Heuristics of the ODE Approach -- 7.3.2 Stability of Differential Equations -- 7.3.3 The Direct Approach of Lyapunov -- 7.3.4 The Indirect Method of Lyapunov -- 7.4 Lattice Gradient Descent Algorithm -- 7.5 Simplified Gradient Calculation -- 7.6 A Partial Gradient Algorithm -- 7.6.1 ODE for the Partial Gradient Algorithm -- 7.6.2 Algorithm Development -- 7.7 A Simplified Partial Gradient Algorithm -- 7.8 Alternate Formulae for the Rotation Angles -- 7.9 On Bounds for the Stepsize Constant µ -- 7.9.1 A Priori and A Posteriori Errors -- 7.9.2 The Ideal Update Formula -- 7.9.3 Linearization About a Minimum Point -- 7.10 Simulation Examples -- Problems -- References -- 8: The Steiglitz-McBride Family of Algorithms -- 8.1 The Steiglitz-McBride Methodology -- 8.2 Off-Line Direct-Form Algorithm -- 8.3 Stationary Points of the Steiglitz-McBride Iteration -- 8.4 Influence of the Disturbance Term -- 8.5 Interpolation Constraints for the White Noise Input Case -- 8.6 Adaptive Filtering Algorithm: Direct Form -- 8.6.1 ODE for the Direct Form Algorithm -- 8.6.2 Convergence in the Sufficient-Order Case -- 8.7 A Lattice Version of the Steiglitz-McBride Iteration -- 8.8 Stationary Points of the Lattice Steiglit-McBride Iteration -- 8.8.1 Equivalence with Direct Form for General Inputs -- 8.8.2 Equivalence for White Noise Input Case -- 8.9 An A Priori Error Bound for White Noise Inputs -- 8.9.1 Eigenvalue Bound for Disturbance-Induced Term.
505 8 $a8.9.2 Eigenvalue Bound for the Signal-Induced Term -- 8.10 On-Line Lattice Algorithm -- 8.10.1 Associated Differential Equation -- 8.11 Simulation Examples -- 8.12 Closing Remarks -- Problems -- References -- 9: Hyperstable Algorithms -- 9.1 Hyperstability Theorem -- 9.1.1 Positive Real Functions -- 9.1.2 Passive Impedance Functions -- 9.1.3 Spectral Factorization -- 9.1.4 Proof of Hyperstability Theorem -- 9.2 Hyperstability and Adaptive Filtering -- 9.3 A Simplified Hyperstable Algorithm -- 9.4 The Associated Differential Equation -- 9.5 A Lattice Version of SHARE -- 9.6 Relaxation of the SPR Condition -- 9.7 The Undermodelled Case -- 9.7.1 Stationary Points for General Inputs -- 9.7.2 White Noise Input Case -- Problems -- References -- 10: Adaptive Notch Filters -- 10.1 Introduction -- 10.2 Basic Principles -- 10.3 Notch Filter Approximations -- 10.3.1 Direct Form Notch Filter -- 10.3.2 Lattice Notch Filter -- 10.4 Gradient Descent Algorithms -- 10.5 A Simplified Lattice Algorithm -- 10.6 Pseudo Least-Squares Algorithms -- 10.7 Multiple Sinusoid Case -- 10.7.1 Gradient Descent Algorithms -- 10.7.2 Simplified Lattice Algorithm -- References -- Problems -- 11: Perspectives and Open Problems -- 11.1 Convergence in the Undermodelled Case -- 11.2 Szegö Polynomials -- 11.3 Spectrally Weighted L2 Criterion -- 11.4 Spectrally Weighted Balanced Systems -- 11.5 Weighted Hankel Forms -- 11.5.1 Hankel-Toeplitz Equations -- 11.5.2 Data-Driven Interpretation -- 11.6 Spectral Extensions of the Shift Operator -- 11.6.1 Spectrally Weighted Shift Operator -- 11.6.2 Prefiltered Signal Interpretation -- References -- Appendix A: Computations with Lattice Filters -- Appendix B: List of Notations -- Index.
520 $a"This unique reference/text integrates rational approximation with adaptive filtering - providing viable, numerically reliable procedures for creating adaptive infinite impulse response (IIR) filters and addressing the choice of filter structure to adapt, algorithm design, and the approximation properties for each type of algorithm. It recasts the theory of adaptive IIR filters by concentrating on recursive lattice filters - freeing systems from the need for direct-form filters." "Generously illustrated, Adaptive IIR Filtering in Signal Processing and Control is a practical daily reference for electrical and electronics, optical, telecommunications, control, digital or signal processing, and computer engineers; filter designers; and computer scientists; as well as an invaluable text for upper-level undergraduate and graduate-level students studying adaptive IIR filtering and system identification."--Jacket.
650 0 $aAdaptive signal processing$xMathematics.
650 0 $aAdaptive filters.
650 0 $aRecursive functions.
650 6 $aTraitement adaptatif du signal$xMathématiques.
650 6 $aFiltres adaptatifs.
650 6 $aFonctions récursives.
650 7 $aAdaptive filters.$2fast$0(OCoLC)fst00796492
650 7 $aAdaptive signal processing$xMathematics.$2fast$0(OCoLC)fst00796497
650 7 $aRecursive functions.$2fast$0(OCoLC)fst01091984
650 7 $aAdaptive Signalverarbeitung$2gnd
650 7 $aAdaptives Filter$2gnd
650 7 $aRekursive Funktion$2gnd
650 17 $aAdaptieve regelaars.$2gtt
650 17 $aFiltering (signalen)$2gtt
650 17 $aRecursieve functies.$2gtt
655 0 $aElectronic book.
655 4 $aElectronic books.
710 2 $aCRC Press LLC.
776 08 $cOriginal$z0824792890$z9780824792893$z0824774922$z9780824774929$w(DLC) 94030294$w(OCoLC)30893939
830 0 $aElectrical engineering and electronics ;$v90.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio14747723$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS