IIR filters designing by water wave optimization

Digital IIR filter design problem is a crucial research issue in control and signal processing. From the viewpoint of optimization, IIR filter designing problems can be formulated as a multi-modal optimization problem with multiple decision variables. This study investigate the feasibility of applying a newly proposed optimization method labeled as water wave optimization (WWO) algorithm to identify the unknown parameters for IIR filter. To enhance its fine (local) searching performance of WWO, Nelder-Mead simplex algorithm based local improvement is incorporated into WWO so as to continually search for the global optima through the reflection, expansion, contraction, and shrink operators. By working on well-known IIR designing benchmark problems, we evaluate the effectiveness and efficacy of the proposed improved WWO algorithm. Experimental results as well as the comparisons with some state-of-the-art algorithm illustrate merit of the hybrid algorithm in which the local search and global search are well balanced.