Convergence Analysis of the Particle Swarm Optimization Based on Stochastic Processes

This paper analyzes the global convergence of the particle swarm optimization algorithm(PSO).Based on the assumption of the previous articles and the theory of stochastic processes,this paper presents a sufficient condition for the system mean-square to be stable.The proposed condition overcomes the disadvantage of the previous studies on PSO for the linear time-varying discrete systems.Compared with the methods in the previous literature,the proposed method achieves better results.Simulations demonstrate the validity of the proposed method.

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