DocumentCode :
3232000
Title :
The optimized estimation of impulse response function using PSO
Author :
Yu, Zhou ; Xingkui, Zhao ; Ye Qingwei ; Zhan Qing ; Haigang, Hu
Author_Institution :
Inf. Sci. & Eng. Coll., Ningbo Univ., Ningbo, China
fYear :
2010
fDate :
23-26 Sept. 2010
Firstpage :
354
Lastpage :
358
Abstract :
A new estimation algorithm of impulse response function is put forward using PSO in this paper. Takes all points of impulse response function as one particle, and searches the best particle with PSO iterations. The evaluation function of PSO iterations is designed to satisfy the convolution equation of the linear vibration system, which requires the minimum sum of errors between the best impulse response function and the response signal with the impulse signal. And the smoothness of impulse response function and the consistency of frequency curves are considered in the design of the PSO evaluation function. The multi-mutation PSO iterations are used, which can avoid falling into the local optimal result. The simulating experiments indicate that the optimized estimation algorithm of impulse response function can work more stably and accurately than the related coefficient algorithm of impulse response function.
Keywords :
convolution; estimation theory; iterative methods; particle swarm optimisation; transient response; vibrations; PSO evaluation function; convolution equation; frequency curves; impulse response function; impulse signal; linear vibration system; multimutation PSO iterations; optimized estimation algorithm; response signal; Integrated circuits; Signal to noise ratio; Impulse response function; particle swarm; structural system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
Type :
conf
DOI :
10.1109/BICTA.2010.5645303
Filename :
5645303
Link To Document :
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