Optimization of IIR digital filters using Particle Swarm Optimization
Ranjit Singh, Sandeep Kumar Arya · 2012
An artificial intelligence approach for the design of infinite-impulse response (IIR) digital filters through Particle Swarm Optimization (PSO) is presented. IIR filter is essentially a digital filter with Recursive responses. Since the error surface of digital IIR filters is generally nonlinear and multimodal, so global optimization techniques are required in order to avoid local minima. This Paper is based on a heuristic way for the designing IIR filters. PSO is a powerful global optimization algorithm introduced in combinatorial optimization problems. This paper finds the optimum coefficients of IIR digital filter through PSO. It is found that the calculated values are more optimal than fda tool and GA available for the design of filter in MATLAB. Design of Low-pass and High-pass IIR digital filter is proposed to provide estimate of transition band. The simulation results of the employed examples shows an improvement on transition band. The stability of designed filters is described by the position of Pole-Zeros.