Fast recursive least squares adaptive second-order volterra filter and its performance analysis

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Publication Type Journal Article
School or College College of Engineering
Department Electrical & Computer Engineering
Creator Mathews, V. John
Other Author Lee, Junghsi
Title Fast recursive least squares adaptive second-order volterra filter and its performance analysis
Date 1993
Description Abstract-This paper presents a fast, recursive least squares (RLS) adaptive nonlinear filter. The nonlinearity is modeled using a second-order Volterra series expansion. The structure presented in the paper makes use of the ideas of fast RLS multichannel filters and has a computational complexity of 0 (N') multiplications per time instant where N - 1 represents the memory span in number of samples of the nonlinear system model. This compares with 0 (N 6) multiplications required for direct implementation. A theoretical performance analysis of the steady-state behavior of the adaptive filter operating in both stationary and nonstationary environments is presented in the paper. The analysis shows that, when the input is zero mean, Gaussian distributed, and the adaptive filter is operating in a stationary environment, the steady-state excess mean-squared error due to the coefficient noise vector is independent of the statistics of the input signal. The results of several simulation experiments are included in the paper. These results show that the adaptive Volterra filter performs well in a variety of situations. Furthermore, the steady-state behavior predicted by the analysis is in very good agreement with the experimental results.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Volume 41
Issue 3
First Page 1087
Last Page 1102
Language eng
Bibliographic Citation Lee, J., & Mathews, V. J. (1993). Fast recursive least squares adaptive second-order volterra filter and its performance analysis. IEEE Transactions on Signal Processing, 41(3), 1087-102. March.
Rights Management (c) 1993 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 1,384,242 bytes
Identifier ir-main,15078
ARK ark:/87278/s686312h
Setname ir_uspace
Date Created 2012-06-13
Date Modified 2021-05-06
ID 707098
Reference URL https://collections.lib.utah.edu/ark:/87278/s686312h
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