Adaptive filters:
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Hoboken, N.J.
Wiley-Interscience
c2008
|
| Schlagworte: | |
| Online-Zugang: | DE-92 DE-898 FHa01 DE-861 DE-473 DE-706 DE-29 URL des Erstveröffentlichers |
| Beschreibung: | Includes bibliographical references (p. 758-774) and indexes Cover13; -- Title13; -- Copyright13; -- Dedication13; -- Contents13; -- Preface -- Notation -- Acknowledgments -- Background Material 13; -- A Random Variables -- A.1 Variance of a Random Variable -- A.2 Dependent Random Variables -- A.3 Complex-Valued Random Variables -- A.4 Vector-Valued Random Variables -- A.5 Gaussian Random Vectors -- B Linear Algebra -- B.1 Hermitian and Positive-Definite Matrices -- B.2 Range Spaces and Nullspaces of Matrices -- B.3 Schur Complements -- B.4 Cholesky Factorization -- B.5 QR Decomposition -- B.6 Singular Value Decomposition -- B.7 Kronecker Products -- C Complex Gradients -- C.1 Cauchy-Riemann Conditions -- C.2 Scalar Arguments -- C.3 Vector Arguments -- Part I: Optimal Estimation13; -- 113;Scalar-Valued Data -- 1.1 Estimation Without Observations -- 1.2 Estimation Given Dependent Observations -- 1.3 Orthogonality Principle -- 1.4 Gaussian Random Variables -- 213;Vector-Valued Data -- 2.1 Optimal Estimator in the Vector Case -- - 2.2 Spherically Invariant Gaussian Variables -- 2.3 Equivalent Optimization Criterion -- Summary and Notes -- Problems and Computer Projects -- Part II: Linear Estimation13; -- 3 Normal Equations13; -- 3.1 Mean-Square Error Criterion -- 3.2 Minimization by Differentiation -- 3.3 Minimization by Completion-of-Squares -- 3.4 Minimization of the Error Covariance Matrix -- 3.5 Optimal Linear Estimator -- 4 Orthogonality Principle13; -- 4.1 Design Examples -- 4.2 Orthogonality Condition -- 4.3 Existence of Solutions -- 4.4 Nonzero-Mean Variables -- 5 Linear Models13; -- 5.1 Estimation using Linear Relations -- 5.2 Application: Channel Estimation -- 5.3 Application: Block Data Estimation -- 5.4 Application: Linear Channel Equalization -- 5.5 Application: Multiple-Antenna Receivers -- 6 Constrained Estimation13; -- 6.1 Minimum-Variance Unbiased Estimation -- 6.2 Example: Mean Estimation -- 6.3 Application: Channel and Noise Estimation -- 6.4 Application: Decision Feedback Equalization -- - 6.5 Application: Antenna Beamforming -- 7 Kalman Filter13; -- 7.1 Innovations Process -- 7.2 State-Space Model -- 7.3 Recursion for the State Estimator -- 7.4 Computing the Gain Matrix -- 7.5 Riccati Recursion -- 7.6 Covariance Form -- 7.7 Measurement and Time-Update Form -- Summary and Notes -- Problems and Computer Projects -- Part III: Stochastic Gradient Algorithms13; -- 8 Steepest8211;Descent Technique13; -- 8.1 Linear Estimation Problem -- 8.2 Steepest-Descent Method -- 8.3 More General Cost Functions -- 9 Transient Behavior13; -- 9.1 Modes of Convergence -- 9.2 Optimal Step-Size -- 9.3 Weight-Error Vector Convergence -- 9.4 Time Constants -- 9.5 Learning Curve -- 9.6 Contour Curves of the Error Surface -- 9.7 Iteration-Dependent Step-Sizes -- 9.8 Newton8217;s Method -- 10 LMS Algorithm13; -- 10.1 Motivation -- 10.2 Instantaneous Approximation -- 10.3 Computational Cost -- 10.4 Least-Perturbation Property -- 10.5 Application: Adaptive Channel Estimation -- - 10.6 Application: Adaptive Channel Equalization -- 10.7 Application: Decision-Feedback Equalization -- 10.8 Ensemble-Average Learning Curves -- 11 Normalized LMS Algorithm13; -- T$137 Adaptive filtering is a topic of immense practical and theoretical value, having applications in areas ranging from digital and wireless communications to biomedical systems. Now, preserving the style and main features of the earlier award-winning publication, "Fundamentals of Adaptive Filtering" (2005 Terman Award), the author offers readers and instructors a concentrated, systematic, and up-to-date treatment of the subject in this valuable new book. "Adaptive Filters" allows readers to gain a gradual and solid introduction to the subject, its applications to a variety of topical problems, existing limitations, and extensions of current theories. This book consists of eleven parts - each part containing a series of focused lectures and ending with bibliographic comments, problems, and computer projects with MATLAB[registered] solutions available to all readers. Additional features include: numerous tables, figures, and projects; special focus on geometric constructions, physical intuition, linear-algebraic concepts, and vector notation; background material on random variables, linear algebra, and complex gradients collected in three introductory chapters; and, complete solutions manual available for instructors MATLAB[registered] solutions available for all computer projects. "Adaptive Filters" offers a fresh, focused look at the subject in a manner that will entice students, challenge experts, and appeal to practitioners and instructors |
| Beschreibung: | 1 Online-Ressource (xxx, 786 p.) |
| ISBN: | 9780470374122 9780470374115 |
Internformat
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| 500 | |a Includes bibliographical references (p. 758-774) and indexes | ||
| 500 | |a Cover13; -- Title13; -- Copyright13; -- Dedication13; -- Contents13; -- Preface -- Notation -- Acknowledgments -- Background Material 13; -- A Random Variables -- A.1 Variance of a Random Variable -- A.2 Dependent Random Variables -- A.3 Complex-Valued Random Variables -- A.4 Vector-Valued Random Variables -- A.5 Gaussian Random Vectors -- B Linear Algebra -- B.1 Hermitian and Positive-Definite Matrices -- B.2 Range Spaces and Nullspaces of Matrices -- B.3 Schur Complements -- B.4 Cholesky Factorization -- B.5 QR Decomposition -- B.6 Singular Value Decomposition -- B.7 Kronecker Products -- C Complex Gradients -- C.1 Cauchy-Riemann Conditions -- C.2 Scalar Arguments -- C.3 Vector Arguments -- Part I: Optimal Estimation13; -- 113;Scalar-Valued Data -- 1.1 Estimation Without Observations -- 1.2 Estimation Given Dependent Observations -- 1.3 Orthogonality Principle -- 1.4 Gaussian Random Variables -- 213;Vector-Valued Data -- 2.1 Optimal Estimator in the Vector Case -- | ||
| 500 | |a - 2.2 Spherically Invariant Gaussian Variables -- 2.3 Equivalent Optimization Criterion -- Summary and Notes -- Problems and Computer Projects -- Part II: Linear Estimation13; -- 3 Normal Equations13; -- 3.1 Mean-Square Error Criterion -- 3.2 Minimization by Differentiation -- 3.3 Minimization by Completion-of-Squares -- 3.4 Minimization of the Error Covariance Matrix -- 3.5 Optimal Linear Estimator -- 4 Orthogonality Principle13; -- 4.1 Design Examples -- 4.2 Orthogonality Condition -- 4.3 Existence of Solutions -- 4.4 Nonzero-Mean Variables -- 5 Linear Models13; -- 5.1 Estimation using Linear Relations -- 5.2 Application: Channel Estimation -- 5.3 Application: Block Data Estimation -- 5.4 Application: Linear Channel Equalization -- 5.5 Application: Multiple-Antenna Receivers -- 6 Constrained Estimation13; -- 6.1 Minimum-Variance Unbiased Estimation -- 6.2 Example: Mean Estimation -- 6.3 Application: Channel and Noise Estimation -- 6.4 Application: Decision Feedback Equalization -- | ||
| 500 | |a - 6.5 Application: Antenna Beamforming -- 7 Kalman Filter13; -- 7.1 Innovations Process -- 7.2 State-Space Model -- 7.3 Recursion for the State Estimator -- 7.4 Computing the Gain Matrix -- 7.5 Riccati Recursion -- 7.6 Covariance Form -- 7.7 Measurement and Time-Update Form -- Summary and Notes -- Problems and Computer Projects -- Part III: Stochastic Gradient Algorithms13; -- 8 Steepest8211;Descent Technique13; -- 8.1 Linear Estimation Problem -- 8.2 Steepest-Descent Method -- 8.3 More General Cost Functions -- 9 Transient Behavior13; -- 9.1 Modes of Convergence -- 9.2 Optimal Step-Size -- 9.3 Weight-Error Vector Convergence -- 9.4 Time Constants -- 9.5 Learning Curve -- 9.6 Contour Curves of the Error Surface -- 9.7 Iteration-Dependent Step-Sizes -- 9.8 Newton8217;s Method -- 10 LMS Algorithm13; -- 10.1 Motivation -- 10.2 Instantaneous Approximation -- 10.3 Computational Cost -- 10.4 Least-Perturbation Property -- 10.5 Application: Adaptive Channel Estimation -- | ||
| 500 | |a - 10.6 Application: Adaptive Channel Equalization -- 10.7 Application: Decision-Feedback Equalization -- 10.8 Ensemble-Average Learning Curves -- 11 Normalized LMS Algorithm13; -- T$137 | ||
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| id | DE-604.BV040769122 |
| illustrated | Not Illustrated |
| indexdate | 2024-08-01T12:12:42Z |
| institution | BVB |
| isbn | 9780470374122 9780470374115 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025747540 |
| oclc_num | 1185785187 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM DE-573 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-861 DE-706 DE-898 DE-BY-UBR DE-29 DE-92 DE-Aug4 |
| owner_facet | DE-91 DE-BY-TUM DE-573 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-861 DE-706 DE-898 DE-BY-UBR DE-29 DE-92 DE-Aug4 |
| physical | 1 Online-Ressource (xxx, 786 p.) |
| psigel | ZDB-35-WIC ZDB-35-WEL FHI_PDA_WIC_Kauf FWS_PDA_WIC_Kauf UBY_PDA_WIC_Kauf FRO_PDA_WIC UBG_PDA_WIC FHR_PDA_WIC_Kauf FHA_PDA_WIC_Kauf ZDB-35-WIC FHR_PDA_WIC_Kauf ZDB-35-WIC FHa_PDA_WIC_Kauf ZDB-35-WIC FRO_PDA_WIC ZDB-35-WIC UBG_PDA_WIC ZDB-35-WIC UBY_PDA_WIC ZDB-35-WIC UER_PDA_WIC_Kauf |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Wiley-Interscience |
| record_format | marc |
| spellingShingle | Adaptive filters TECHNOLOGY & ENGINEERING / Electronics / Circuits / Integrated bisacsh TECHNOLOGY & ENGINEERING / Electronics / Circuits / General bisacsh Adaptive filters TECHNOLOGY & ENGINEERING / Electronics / Circuits / Integrated / bisacsh TECHNOLOGY & ENGINEERING / Electronics / Circuits / General / bisacsh Adaptives Filter (DE-588)4141377-5 gnd |
| subject_GND | (DE-588)4141377-5 |
| title | Adaptive filters |
| title_auth | Adaptive filters |
| title_exact_search | Adaptive filters |
| title_full | Adaptive filters Ali H. Sayed |
| title_fullStr | Adaptive filters Ali H. Sayed |
| title_full_unstemmed | Adaptive filters Ali H. Sayed |
| title_short | Adaptive filters |
| title_sort | adaptive filters |
| topic | TECHNOLOGY & ENGINEERING / Electronics / Circuits / Integrated bisacsh TECHNOLOGY & ENGINEERING / Electronics / Circuits / General bisacsh Adaptive filters TECHNOLOGY & ENGINEERING / Electronics / Circuits / Integrated / bisacsh TECHNOLOGY & ENGINEERING / Electronics / Circuits / General / bisacsh Adaptives Filter (DE-588)4141377-5 gnd |
| topic_facet | TECHNOLOGY & ENGINEERING / Electronics / Circuits / Integrated TECHNOLOGY & ENGINEERING / Electronics / Circuits / General Adaptive filters TECHNOLOGY & ENGINEERING / Electronics / Circuits / Integrated / bisacsh TECHNOLOGY & ENGINEERING / Electronics / Circuits / General / bisacsh Adaptives Filter |
| url | https://onlinelibrary.wiley.com/doi/book/10.1002/9780470374122 |
| work_keys_str_mv | AT sayedalih adaptivefilters |