Weighted Myriad Filter Implementation with Genetic Algorithm in -Stable Noise Environments

Yang Jun; Ma Xiao-yan; Wan Shan-hu

Volume 26 Issue 1

Jan. 2004

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Yang Jun, Ma Xiao-yan, Wan Shan-hu. Weighted Myriad Filter Implementation with Genetic Algorithm in -Stable Noise Environments[J]. Journal of Electronics & Information Technology, 2004, 26(1): 82-88.

Citation:

Yang Jun, Ma Xiao-yan, Wan Shan-hu. Weighted Myriad Filter Implementation with Genetic Algorithm in -Stable Noise Environments[J]. Journal of Electronics & Information Technology, 2004, 26(1): 82-88.

Yang Jun, Ma Xiao-yan, Wan Shan-hu. Weighted Myriad Filter Implementation with Genetic Algorithm in -Stable Noise Environments[J]. Journal of Electronics & Information Technology, 2004, 26(1): 82-88.

Citation:

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Weighted Myriad Filter Implementation with Genetic Algorithm in -Stable Noise Environments

Yang Jun^{①②;马晓岩},
Ma Xiao-yan,
Wan Shan-hu

Received Date: 2002-07-11
Rev Recd Date: 2003-01-09
Publish Date: 2004-01-19

Abstract

Abstract

A novel algorithm is proposed based on the genetic theory, which has global optimum searching characteristic. Meanwhile, considering its computational cost, decimal code, not binary one is used in operation of the operators. Moreover, a modified adaptive weights training algorithm is also used to resolve the weights fluctuant problem in stable range. Numerical simulations demonstrate that tlie genetic algorithm can converge at the global extremum quickly, and that weights estimation with the modified adaptive weights training algorithm have a more stable range, and the filtering performance has been improved obviously.

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References(1)

References

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