The Study And Application Of Adaptive Filter Based On Particle Swarm Optimization Algorithm

Adaptive Filtering is the most important part of the digital signal processing technique, having special function to the processing of complicated signal。In the actual digital signal system, the noise which adds in the signal usually isn't single Gauss noise, but linear filter requests medium degree noise excursion, making the filter function of the non- Gauss noise descend. In order to overcome the weakness of the linear filtering, usually adopt non-linear filtering. To meet the need of the adaptive filtering real-time, in this paper introduce a kind of artificial neural networks with a high degree of parallel processing ability to achieve adaptive non-linear filtering.Particle swarm optimization (PSO) algorithm is a kind of evolution computing technique based on swarm intelligence algorithms. To other evolutionary algorithms, its convergence's speed is fast, rules are simple, and it is easy to implement programming. In order to restrain particles from trapping in local optimum, the improved PSO algorithm is leading into the mutation operator according on standard derivation of swarm fit value. The algorithm gets away from the bondage of local optimum, raises the accuracy of non-linear optimization and keeps PSO algorithm's structure simple in the meantime. In this paper, the improved PSO algorithm optimizates artificial neural networks.In this paper the adaptive filter based on PSO algorithm is designed, and applies it to the adaptive noise canceller to process the sine signal which blends to have noise. We discover that the improved PSO algorithm has a very strong processing capacity and optimization capacity. Compared with the traditional BP algorithm, using it to optimize the power value of neural networks can save a great deal of study and calculation time, enhance signal noise ratio at the same time and further to meet the real-time processing requirements of adaptive filter. This paper sets up an Adaptive Noise Cancellation Controller based on PSO algorithm, which is proved to be more efficient in the noise cancellation by Simulink.