Stochastic mean-square performance analysis of an adaptive Hammerstein filter

Update Item Information
Publication Type journal article
School or College College of Engineering
Department Electrical & Computer Engineering
Creator Mathews, V. John
Other Author Jeraj Janez
Title Stochastic mean-square performance analysis of an adaptive Hammerstein filter
Date 2006
Description Abstract-This paper presents an almost sure mean-square performance analysis of an adaptive Hammerstein filter for the case when the measurement noise in the desired response signal is a martingale difference sequence. The system model consists of a series connection of a memoryless nonlinearity followed by a recursive linear filter. A bound for the long-term time average of the squared a posteriori estimation error of the adaptive filter is derived using a basic set of assumptions on the operating environment. This bound consists of two terms, one of which is proportional to a parameter that depends on the step size sequences of the algorithm and the other that is inversely proportional to the maximum value of the increment process associated with the coefficients of the underlying system. One consequence of this result is that the long-term time average of the squared a posteriori estimation error can be made arbitrarily close to its minimum possible value when the underlying system is time-invariant.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Volume 54
Issue 6
First Page 2168
Last Page 2177
Language eng
Bibliographic Citation Jeraj, J., & Mathews, V. J. (2006). Stochastic mean-square performance analysis of an adaptive Hammerstein filter. IEEE Transactions on Signal Processing, 54(6), 2168-77. June.
Rights Management (c) 2006 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 354,517 bytes
Identifier ir-main,15104
ARK ark:/87278/s60p1hm2
Setname ir_uspace
ID 706718
Reference URL https://collections.lib.utah.edu/ark:/87278/s60p1hm2
Back to Search Results