“…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.…”