Abstract
Based on the study of Particle Swarm Optimization (PSO) on the mechanism of information communion, a new adaptive method of PSO is presented in this paper. This new adaptive method is to avoid the particles getting into local best solution during the optimization. By applying Adaptive Particle Swarm Optimization (APSO) to optimize transition sample values in FIR filter, the maximum stop band attenuation is obtained. The simulations of designing low-pass FIR have been done and the simulation results show that APSO is better than PSO not only in the optimum ability but also in the convergence speed.
This work is supported by the National Natural Science Foundation of China under the Grant No.60474064.
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Huang, W., Zhou, L., Qian, J., Ma, L. (2005). FIR Frequency Sampling Filters Design Based on Adaptive Particle Swarm Optimization Algorithm. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_34
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DOI: https://doi.org/10.1007/11539902_34
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