NDLI: Application of a Minimum-Disturbance Description to Constrained Adaptive Filters

Content Provider	IEEE Xplore Digital Library
Author	Castoldi, F.T. de Campos, M.L.R.
Copyright Year	1994
Abstract	The development of adaptive filters is usually based either on a stochastic approximation of the gradient vector and the Hessian matrix, or on a deterministic minimization of quadratic a posteriori output errors. This paper investigates the design of adaptation algorithms by means of a minimum-disturbance approach together with added constraints. More than just rewriting objective functions minimized by the algorithms, the approach provides insight and extra tools for optimizing with respect to other parameters, e.g., the convergence factor μ. Designing new algorithms by adding extra costs or constraints to the objective function follows naturally, whereas the main characteristics of the algorithms remain clear. Understanding subtleties that set similar algorithms apart is also made easier. We apply the method to known algorithms, such as the LMS and RLS algorithms, and also to their variants. Rather than proposing a new algorithm, we hope this article will facilitate the development of different algorithms to meet the challenges posed by demanding applications. In addition, ensuing discussions may help understanding better the behavior of each algorithm in a particular scenario.
Sponsorship	IEEE Signal Processing Society
Starting Page	1215
Ending Page	1218
Page Count	4
File Size	587924
File Format	PDF
ISSN	10709908
Volume Number	20
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing algorithms Equations Algorithm design and analysis Mathematical model Linear programming Least squares approximations Approximation algorithms optimization methods Adaptive filters adaptive signal processing minimum-disturbance description
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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