NDLI: Piecewise Volterra filters based on the threshold decomposition operator

Content Provider	IEEE Xplore Digital Library
Author	Heredia, E.A. Arce, G.R.
Copyright Year	1996
Description	Author affiliation: Dept. of Electr. Eng., Delaware Univ., Newark, DE, USA (Heredia, E.A.)
Abstract	We report our results concerning the study of multivariate functions of threshold-decomposed signals. In particular we show that multilinear tensor forms of the decomposed signal yield a class of filters that we propose to call piecewise Volterra filters (PWV). A filter can be viewed as a transformation of /spl Rscr//sup N//spl rarr//spl Rscr/, where N is the number of filter taps. PWV filters partition /spl Rscr//sup N/ using a hyper-rectangular lattice, and assign a Volterra filter to each of the partition regions. At the partition boundaries continuity between the multivariate polynomials is preserved resulting in class /spl Cscr//sup 0/ piecewise polynomials. PWV filters constitute an efficient alternative for describing some systems rich in hard nonlinear structures, especially since parameter estimation remains a linear problem for PWVs.
Starting Page	1593
Ending Page	1596
File Size	471776
Page Count	4
File Format	PDF
ISBN	0780331923
ISSN	15206149
DOI	10.1109/ICASSP.1996.544107
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-05-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Polynomials Nonlinear filters Tensile stress Parameter estimation Linearity Piecewise linear approximation Adaptive filters Lattices Nonlinear systems Filtering theory
Content Type	Text
Resource Type	Article

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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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