A Multi-modal Immune Optimization Algorithm for IIR Filter Design

Adaptive infinite-impulse-response (IIR) filter provides a powerful approach for solving a variety of practical problems. However, they might have a multi-modal error surface and their design is formulated as a highly nonlinear optimization problem. By integrating chaos mechanism and niche technique, a novel immune optimization algorithm based on the clonal selection principle and idiotypic immune network theory exhibited in biological immune system with global optimization ability, called multi-modal immune optimization algorithm(MIOA), is proposed for digital IIR filter design in this paper. Taking advantages of the ergodic and stochastic properties of chaotic variable, an adaptive chaos mutation operator is designed by the combination of prior knowledge of antibody and evolution iterations, the new algorithm has the advantage of preventing from prematurity and fast convergence speed. Simulation results show that the proposed approach is accurate and has a fast convergence rate, and the results obtained demonstrate that the proposed method can be efficiently used for digital IIR filter design.