NDLI: SHARF convergence properties

Content Provider	IEEE Xplore Digital Library
Author	Johnson Jr., C. Larimore, M. Treichler, J. Anderson, B.
Copyright Year	1974
Abstract	A class of stable algorithms for adapting infinite impulse response (IIR) digital filters based on the concepts of nonlinear stability theory prominent in the control literature is emerging. While this class of adaptive filters offers much promise in practical applications, little has been done toward providing a characterization that would guide selection of design parameters such as adaptation constants and error smoothing coefficients. This paper focuses on the simplest well-behaved member of this class of adaptive recursive filters, SHARF. Progression from a local linearization of the nonlinear parameter estimate convergence behavior, through an idealized eigenvalue/eigenvector analysis of the parameter estimate time-varying recursion, to Lyapunov function establishment for the full output and parameter error system reveals the exponential, local, nongradient descent convergence character of SHARF and provides initial insight into the effects of adaptation constants and error smoothing coefficients on these characteristics.
Starting Page	659
Ending Page	670
Page Count	12
File Size	1337848
File Format	PDF
ISSN	00963518
Volume Number	29
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1981-06-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Convergence Adaptive filters Smoothing methods Parameter estimation Recursive estimation IIR filters Digital filters Stability Eigenvalues and eigenfunctions Time varying systems
Content Type	Text
Resource Type	Article
Subject	Signal Processing

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