Adaptive volterra filters using orthogonal structures

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Publication Type Journal Article
School or College College of Engineering
Department Electrical & Computer Engineering
Creator Mathews, V. John
Title Adaptive volterra filters using orthogonal structures
Date 1996
Description Abstract-This paper presents an adaptive Volterra filter that empolys a recently developed orthogonalization procedure of Gaussian signals for Volterra system identification. The algorithm is capable of handling arbitrary orders of nonlinearity P as well as arbitrary lengths of memory N for the system model. The adaptive filter consists of a linear lattice predictor of order N, a set of GramSchmidt orthogonalizers for N vectors of size P+1 elements each, and a joint process estimator in which each coefficient is adapted individually. The complexity of implementing this adaptive filter is comparable to the complexity of the system model when N is much larger than P, a condition that is true in many practical situations. Experimental results demonstrating the capabilities of the algorithm are also presented in the paper.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Volume 3
Issue 12
First Page 307
Last Page 309
Language eng
Bibliographic Citation Mathews, V. J. (1996). Adaptive volterra filters using orthogonal structures. IEEE Signal Processing Letters, 3(12), 307-9. December.
Rights Management (c) 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Format Medium application/pdf
Format Extent 318,253 bytes
Identifier ir-main,15087
ARK ark:/87278/s66h51v2
Setname ir_uspace
Date Created 2012-06-13
Date Modified 2021-05-06
ID 705145
Reference URL https://collections.lib.utah.edu/ark:/87278/s66h51v2
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