Parameter Estimation of Bilinear Digital Systems Using Differential Evolution Algorithm

Abstract

In this paper, we propose a novel parameter estimation scheme for bilinear digital systems based on using the differential evolution (DE) algorithm. The DE algorithm is one of evolutionary computations and is fully with real-valued operations during the optimization. It has been proven to be an excellent searching algorithm in solving a variety of practical engineering optimization problems.With the use of the DE algorithm, the parameter estimation problem especially for the bilinear digital system is considered. By minimizing the error signal between the actual output and model output, the system coefficients can accurately be estimated. Finally, a large number of independent runs with different sets of initial conditions are examined to confirm the algorithm's robustness and feasibility.

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

“…The Volterra digital system which is going to be estimated is expressed by Eq. ( 11 (11) where the unknown system parameters are assumed to be Fig. 4.…”

“…The design scheme for solving the parameter estimation problem of Volterra digital system here is the differential evolution (DE) algorithm which has been proven to be an effective and powerful means to various optimization problems, for instances, network traffic forecasting (6) , congestion management (7) , exergoeconomic analysis and optimization of a cogeneration system (8) , workload prediction in cloud (9) , and community detection (10) . In our previous work (11) , the classical DE algorithm was used to successfully solve for parameter estimation of bilinear digital filters. Like those of genetic algorithm, the DE is composed of three evolutionary operations including mutation, crossover, and selection to achieve the optimization purpose.…”