FIR FILTER DESIGN WITH INERTIA WEIGHT AND COMPRESSION FACTOR APPROACH USING ADVANCED OPTIMIZATION TECHNIQUES

Abstract

This paper includes the design of Finite impulse response filter with inertia weight and compression factor approach. The objective function of filter design involves accurate control of various parameters of frequency spectrum and is thus highly non-uniform, non-linear, non-differentiable and multimodal in nature. Classical optimization methods cannot converge to solutions. Because they have disadvantages such as highly sensitive to starting points, frequent convergence to local optimum solution or divergence or revisiting the same solution, requirement of continuous and differentiable objective cost function, requirement of the piecewise linear cost approximation and problem of convergence and algorithm. Evolutionary optimization methods for the design of optimal digital filters have better control of parameters and the highest stop band attenuation.