Improved Chaotic Particle Swarm Optimization using circle map for training SVM

Training SVM consumes large memory and computation time, but traditional methods can not overcome above shortcomings. This paper proposes an improved SVM training method based on chaotic particle swarm optimization (CPSO) using circle map. Firstly, a new chaotic search model using improved circle map is introduced. Then this new model is introduced into particle swarm optimization (PSO). Finally, the detail training SVM algorithm using this improved CPSO algorithm is presented. The experimental results on face database show that the proposed SVM method optimized by the improved CPSO can achieve higher recognition performance.