An Improved Differential Evolution Algorithm to Parameters Estimation of Volterra Digital Systems

Abstract

This paper will present a new parameter estimation method for Volterra digital systems by an improved differential evolution (DE) algorithm. The DE algorithm has been proven to be an efficient means to solve a variety of engineering optimization problems. To further enhance the searching capacity, the chaotic random number produced by the logistic map system is incorporated into the algorithm to replace the mutation constant factor. Based on the improved DE algorithm, the parameter estimation design problem for the Volterra digital systems is considered and solved. Some simulation results will reveal that the proposed design method can exactly solve for all the system parameters.