Title :
Evolving IIR approximants for FIR digital filters
Author :
Rao, Sathyanarayan S. ; Ramasubrahmanyan, Arun
Author_Institution :
Dept. of Electr. & Comput. Eng., Villanova Univ., PA, USA
fDate :
Oct. 30 1995-Nov. 1 1995
Abstract :
This paper describes a new technique for approximating an FIR digital filter by a reduced order IIR filter. The technique yields the globally optimal IIR filter, in the sense of minimizing the output error between the given FIR filter and the IIR approximant to a random white noise input. The model order of the IIR filter can either be specified or it is taken as the one that minimizes the Akaike information criterion. Simulated evolutionary optimization, a multi-agent stochastic search technique is used to optimize the coefficients. The technique permits stipulation of additional constraints on the filter to make it stable, minimum-phase and any other designer specifications. Also being inherently parallel, the technique requires significantly less computation time, compared to algorithms that optimize coefficients serially. Simulation results indicate that the proposed method performs better than classical LMS and system identification based methods like the Stieglitz-McBride method.
Keywords :
FIR filters; Akaike information criterion; FIR digital filters; IIR approximants; globally optimal IIR filter; inherently parallel technique; minimum-phase filter; model order; multi-agent stochastic search technique; random white noise input; reduced order IIR filter; simulated evolutionary optimization; simulation results; stable filter; Chebyshev approximation; Computational modeling; Digital filters; Finite impulse response filter; IIR filters; Least squares approximation; Optimization methods; Simulated annealing; Stochastic resonance; White noise;
Conference_Titel :
Signals, Systems and Computers, 1995. 1995 Conference Record of the Twenty-Ninth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-8186-7370-2
DOI :
10.1109/ACSSC.1995.540845