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Weighted least-squares design of IIR all-pass filters using a Lyapunov error criterion

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4 Author(s)
Yue-Dar Jour ; Dept. of Electr. Eng., ROC Mil. Acad., Kaohsiung, Taiwan ; Fu-Kun Chen ; Lo-Chyuan Su ; Chao-Ming Sun

This paper extends a neural network based architecture for the weighted least-squares design of IIR all-pass filters. The error difference between the desired phase response and the phase of the designed all-pass filter is formulated as a Lyapunov error criterion. The filter coefficients are obtained when neural network achieves convergence by using the corresponding dynamic function. Furthermore, a weighted updating function is proposed to achieve good approximation to the minimax solution. Simulation results indicate that the proposed technique is able to achieve good performance in a parallelism manner.

Published in:

Circuits and Systems (APCCAS), 2010 IEEE Asia Pacific Conference on

Date of Conference:

6-9 Dec. 2010