Title :
Differential evolution particle swarm optimization for digital filter design
Author :
Luitel, Bipul ; Venayagamoorthy, Ganesh K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO
Abstract :
In this paper, swarm and evolutionary algorithms have been applied for the design of digital filters. Particle swarm optimization (PSO) and differential evolution particle swarm optimization (DEPSO) have been used here for the design of linear phase finite impulse response (FIR) filters. Two different fitness functions have been studied and experimented, each having its own significance. The first study considers a fitness function based on the passband and stopband ripple, while the second study considers a fitness function based on the mean squared error between the actual and the ideal filter response. DEPSO seems to be promising tool for FIR filter design especially in a dynamic environment where filter coefficients have to be adapted and fast convergence is of importance.
Keywords :
FIR filters; band-pass filters; band-stop filters; evolutionary computation; linear phase filters; mean square error methods; particle swarm optimisation; FIR filters; differential evolution particle swarm optimization; digital filter design; evolutionary algorithms; filter coefficients; fitness functions; linear phase finite impulse response filters; mean squared error; passband ripple; stopband ripple; Algorithm design and analysis; Band pass filters; Chebyshev approximation; Digital filters; Evolutionary computation; Finite impulse response filter; Frequency; IIR filters; Particle swarm optimization; Passband;
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
DOI :
10.1109/CEC.2008.4631335