Variable step-size LMS adaptive algorithm based on computational verb rules

In this paper, a new variable step-size LMS algorithm based on computational verb rules is presented. This method allows the algorithm to converge faster and to produce smaller steady-state errors compared to other variable step-size LMS algorithms, even when the system is subjected to sudden change...

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Vydáno v:2010 International Conference on Anti-Counterfeiting, Security and Identification s. 343 - 346
Hlavní autoři: Fanfan Zheng, Lianfen Huang, Zhiyuan Shi, Tao Yang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.07.2010
Témata:
Adaptive filters
Algorithm design and analysis
Cognition
computational verb ride
Convergence
filter
Heuristic algorithms
knowledge representation
Least squares approximation
LMS adaptive algorithm
Signal processing algorithms
similarity
ISBN:1424467314, 9781424467310
ISSN:2163-5048
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Shrnutí:In this paper, a new variable step-size LMS algorithm based on computational verb rules is presented. This method allows the algorithm to converge faster and to produce smaller steady-state errors compared to other variable step-size LMS algorithms, even when the system is subjected to sudden changes. Furthermore, it provides a brand new framework that allows the designers to design adaptive algorithms in a simpler and more effective way by using computational verb rules to encode the designers' knowledge of dynamical processes. Simulation results are provided to show the usefulness of the proposed algorithm by comparing with other variable step-size LMS algorithms.
ISBN:1424467314
9781424467310
ISSN:2163-5048
DOI:10.1109/ICASID.2010.5551355