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 1995
Description Abstract- This paper presents an adaptive Volterra filter that employs 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 or order N, a set of Gram-Schmidt orthogonalizers for N vectors of size P + 1 elements each, and a joint process estimator in which each coefficient is adaptive 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. (1995). Adaptive volterra filters using orthogonal structures. Proceedings of ICASSP 95, 3(12), 307-9. May.
Rights Management (c) 1998 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 259,102 bytes
Identifier ir-main,15150
ARK ark:/87278/s6g16j6s
Setname ir_uspace
Date Created 2012-06-13
Date Modified 2021-05-06
ID 704935
Reference URL https://collections.lib.utah.edu/ark:/87278/s6g16j6s
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