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 |