Title :
IIR Model Identification by the Improving WTLMS
Author :
Ouyang Xin-yu ; Zhao Nan-nan ; Chen Xue-bo
Author_Institution :
Dalian Univ. of Technol., Dalian, China
Abstract :
The wavelet transform domain least mean square (WTLMS) is knew to have, in general, a fast convergence rate than the LMS algorithm. Through analysing the redundancy existed in the WTLMS algorithm, how to remove structural redundancy is showed, which in turn reduces the computational load of the algorithm. The method of how to transform the non-causal system into causal system is also given. The simulation results show that the proposed algorithm also could be used to identify the parameters of the IIR filters, and it also show that the improving WTLMS have the higher speed than the WTLMS algorithm .
Keywords :
IIR filters; identification; least mean squares methods; redundancy; wavelet transforms; IIR model identification; causal system; computational load; structural redundancy; wavelet transform domain least mean square; Algorithm design and analysis; Computational intelligence; Computational modeling; Finite impulse response filter; Least squares approximation; Redundancy; Security; Signal processing; Wavelet domain; Wavelet transforms;
Conference_Titel :
Computational Intelligence and Security, 2008. CIS '08. International Conference on
Conference_Location :
Suzhou
Print_ISBN :
978-0-7695-3508-1
DOI :
10.1109/CIS.2008.157