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E-raamat: Adaptive Digital Filters

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  • Formaat: PDF+DRM
  • Ilmumisaeg: 21-Jun-2013
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642335617
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Adaptive Digital FiltersSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 21-Jun-2013
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Keel: eng
  • ISBN-13: 9783642335617
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“Adaptive Digital Filters” presents an important discipline applied to the domain of speech processing. The book first makes the reader acquainted with the basic terms of filtering and adaptive filtering, before introducing the field of advanced modern algorithms, some of which are contributed by the authors themselves. Working in the field of adaptive signal processing requires the use of complex mathematical tools. The book offers a detailed presentation of the mathematical models that is clear and consistent, an approach that allows everyone with a college level of mathematics knowledge to successfully follow the mathematical derivations and descriptions of algorithms. The algorithms are presented in flow charts, which facilitates their practical implementation. The book presents many experimental results and treats the aspects of practical application of adaptive filtering in real systems, making it a valuable resource for both undergraduate and graduate students, and for all others interested in mastering this important field.

Boasting a wealth of experimental results and algorithms as well as a clear exposition of the mathematical background, this introduction to adaptive digital filtering guides the reader from the theoretical fundamentals to real-life technical applications.

Arvustused

From the book reviews:

The volume arose as the product of a scientific activity carried out in some research centers in Serbia, at Belgrade. Firstly, it provides a clear and consistent presentation of the mathematical models underlying the adaptive filtering. The mathematical level corresponds to undergraduate and graduate students in Electrical Engineering, so we conclude that the present volume will be of high interest to this student area. (Dumitru Stanomir, zbMATH, Vol. 1301, 2015)

1 Introduction 1(30)
1.1 Conventional Approach to the Design of Digital Filters
1(8)
1.2 Optimal Filters
9(18)
1.2.1 Wiener Filter
9(7)
1.2.2 Kalman Filter
16(11)
1.3 Adaptive Filters
27(4)
2 Adaptive Filtering 31(44)
2.1 Introduction
31(1)
2.2 Structures of Digital Filters
31(5)
2.2.1 Filters with Infinite Impulse Response (I1R Filters)
32(2)
2.2.2 Filters with Finite Impulse Response (FIR Filters)
34(2)
2.3 Criterion Function for the Estimation of FIR Filter Parameters
36(9)
2.3.1 Mean Square Error (Risk) Criterion: MSE Criterion
37(2)
2.3.2 Minimization of the Criterion of Mean Square Error (Risk)
39(6)
2.4 Adaptive Algorithms for the Estimation of Parameters of FIR Filters
45(14)
2.4.1 Least Mean Square (LMS) Algorithm
46(3)
2.4.2 Least Squares Algorithm (LS Algorithm)
49(2)
2.4.3 Recursive Least Squares (RLS) Algorithm
51(2)
2.4.4 Weighted Recursive Least Squares (WRLS) Algorithm with Exponential Forgetting Factor
53(6)
2.5 Adaptive Algorithms for the Estimation of the Parameters of IIR Filters
59(16)
2.5.1 Recursive Prediction Error Algorithm (RPE Algorithm)
67(5)
2.5.2 Pseudo-Linear Regression (PLR) Algorithm
72(3)
3 Finite Impulse Response Adaptive Filters with Variable Forgetting Factor 75(34)
3.1 Choice of Variable Forgetting Factor
75(26)
3.1.1 Choice of Forgetting Factor Based on the Extended Prediction Error
76(2)
3.1.2 Fortescue-Kershenbaum-Ydstie Algorithm
78(8)
3.1.3 Parallel Adaptation Algorithm (PA-RLS Algorithm)
86(7)
3.1.4 Generalized Weighted Least Squares Algorithm with Variable Forgetting Factor
93(3)
3.1.5 Modified Generalized Likelihood Ratio: MGLR Algorithm
96(5)
3.2 Experimental Analysis
101(8)
3.2.1 Comparative Analysis of Recursive Algorithms for the Estimation of Variable Forgetting Factor (Analysis of RLS Algorithm with EGP, FKY and PA Strategy for the Calculation of Variable Forgetting Factor)
101(8)
4 Finite Impulse Response Adaptive Filters with Increased Convergence Speed 109(38)
4.1 Definition of the Parameter Identification Problem
110(2)
4.2 Finite Impulse Response Adaptive Filters with Optimal Input
112(3)
4.3 Convergence Analysis of Adaptive Algorithms
115(16)
4.4 Application of Recursive Least Squares Algorithm with Optimal Input for Local Echo Cancellation in Scrambling Systems
131(8)
4.4.1 Definition of the Local Echo Cancellation Problem in Scrambling Systems
133(1)
4.4.2 Experimental Analysis
134(5)
4.5 Application of Variable Forgetting Factor to Finite Impulse Response Adaptive Filter with Optimal Input
139(8)
5 Robustification of Finite Impulse Response Adaptive Filters 147(40)
5.1 Robust Least Mean Square Algorithm
149(13)
5.1.1 Robustification of Least Mean Square Algorithm: Robust LMS Algorithm
152(3)
5.1.2 Stability Analysis of Robust Estimators
155(3)
5.1.3 Simulation-Based Experimental Analysis
158(4)
5.2 Robust Recursive Least Squares Algorithm with Optimal Output
162(8)
5.2.1 Experimental Analysis
168(2)
5.3 Adaptive Estimation of the Scaling Factor in Robust Algorithms
170(10)
5.3.1 Experimental Analysis
177(3)
5.4 Robust Recursive Least Squares Algorithm with Variable Forgetting Factor and with Detection of Impulse Noise
180(7)
5.4.1 Experimental Analysis
184(3)
6 Application of Adaptive Digital Filters for Echo Cancellation in Telecommunication Networks 187(18)
6.1 Echo: Causes and Origins
189(7)
6.1.1 Echo in Speech Transmission
189(2)
6.1.2 Acoustic Echo
191(1)
6.1.3 Echo in Data Transfer
192(1)
6.1.4 Basic Principles of Adaptive Echo Cancellation
193(3)
6.2 Mathematical Model of an Echo Cancellation System
196(1)
6.3 Analysis of the Influence of Excitation Signal to the Performance of Echo Cancellation System for Speech Signal Transmission
197(8)
References 205(4)
Index 209
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