From elininating outside interference to separate data stream traveling together, filters are used for a wide range of applications in communications. The Least-Mean-Square (LMS) filter has established itself as the workhorse for the design of linear adaptive systems. This book provides new insights into the behavior of this adaptive filter, presenting detailed treatments of the most recent advances. _ Edited by the original inventor of the technology. _ Includes contributions by the foremost experts in the field. _ The only book to cover these topics together.
From elininating outside interference to separate data stream traveling together, filters are used for a wide range of applications in communications. The Least-Mean-Square (LMS) filter has established itself as the workhorse for the design of linear adaptive systems. This book provides new insights into the behavior of this adaptive filter, presenting detailed treatments of the most recent advances._ Edited by the original inventor of the technology. _ Includes contributions by the foremost experts in the field. _ The only book to cover these topics together.
Produktdetails
Produktdetails
Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control 1
SIMON HAYKIN, PhD, is University Professor and Director of the Adaptive Systems Laboratory at McMaster University. BERNARD WIDROW, PhD, is Professor for Adaptive Systems at Stanford University.
Inhaltsangabe
Contributors. Introduction (Simon Haykin). 1. On the Efficiency of Adaptive Algorithms (Berrnard Widrow and Max Kamenetsky). 2. Travelling-Wave Model of Long LMS Filters (Hans Butterweck). 3. Energy Conservation and the Learning Ability of LMS Adaptive Filters (Ali Sayed & Vitor H. Nascimento). 4. On the Robustness of LMS Filters (Babak Hassibi). 5. Dimension Analysis for Least-Mean-Square Algorithms (Iven M.Y. Mareels, et al.). 6. Control of LMS-Type Adaptive Filters (Eberhard Haensler and Gerhard Uwe Schmidt). 7. Affine Projection Algorithms (Steve Gay). 8. Proportionate Adaptation: New Paradigms in Adaptive Filters (Zhe Chen, et al.). 9. Steady-State Dynamic Weight Behavior in (N)LMS Adaptive Filters (A.A. (Louis) Beex and James R. Zeidler). 10. Error Whitening Wiener Filters: Theory and Algorithms (Jose Principe, et al.). Index.
Contributors. Introduction (Simon Haykin). 1. On the Efficiency of Adaptive Algorithms (Berrnard Widrow and Max Kamenetsky). 2. Travelling-Wave Model of Long LMS Filters (Hans Butterweck). 3. Energy Conservation and the Learning Ability of LMS Adaptive Filters (Ali Sayed & Vitor H. Nascimento). 4. On the Robustness of LMS Filters (Babak Hassibi). 5. Dimension Analysis for Least-Mean-Square Algorithms (Iven M.Y. Mareels, et al.). 6. Control of LMS-Type Adaptive Filters (Eberhard Haensler and Gerhard Uwe Schmidt). 7. Affine Projection Algorithms (Steve Gay). 8. Proportionate Adaptation: New Paradigms in Adaptive Filters (Zhe Chen, et al.). 9. Steady-State Dynamic Weight Behavior in (N)LMS Adaptive Filters (A.A. (Louis) Beex and James R. Zeidler). 10. Error Whitening Wiener Filters: Theory and Algorithms (Jose Principe, et al.). Index.
Rezensionen
"...strongly recommended for researchers working in the field of signal processing and its applications." (IEEE Circuits & Devices, January/February 2006)
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