Research On Non Recurisive Digital Filter Design Based On Particle Swarm Optimization Algorithm

In today’s advanced information society, these information obtained by people are increasing rapidly, so it is necessary to solve these obtained information with the means that is with good performance, and these means are used to serve the social and people’s needs. With the rapidly development of digital signal processing technology, these means are being widely used in the industry field with various forms and have formed a cross-disciplinary applications. In the area of industry, the digital filter is the core of digital signal processing. In the field of digital signal processing, the application of digital filter can not be separated from the extraction, transmission and recovery of signal. The digital filter is essential to secure transmission and flexible processing of signal. In the all electronic systems, the digital filter is the most complex part of the system, and the digital filter is the core of the electronic products, the quality of the digital filter directly determines the quality of these electronic product. Because of the strict linear phase frequency characteristics of Impulse Response(FIR), the non recursive digital filter is also known as the finite impulse response digital filter(Finite). The sequence length of the unit response for the FIR digital filter is limited, which can ensure the system of filter being stable, so the FIR digital filter has a wide range of applications and research prospects.In the design of the actual industrial, there will often face all kinds of optimization problems, and the accurately handle with some problems can be transformed into an optimization problem.The design of the FIR digital filter is to design the sequence of the unit response for it, and the core of the design is to optimize the parameters of the digital filter. In order to deal with all kinds of optimization problems, people are inspired by the principle of bionic principle and present some algorithms that are the genetic algorithm, the ant colony optimization algorithm, the particle swarm optimization algorithm and other optimization problems. In the among of these algorithms, the particle swarm optimization(PSO) is a group search algorithm which simulates the social behavior of birds. Many researchers have attached great importance to it for its simple principle, fast convergence, easy setting of parameters and the efficient when it is used in solving actual problem. In recent years, with the development of evolutionary algorithms and swarm intelligence theory, the particle swarm optimization algorithm is introduced to the auxiliary design of digital filter, and have a good performance in the application.The traditional design method have some disadvantages in the design of FIR digital filter process, such as the accuracy is not high and the side band frequency is difficult to determine. To overcome these disadvantages, the particle swarm algorithm and its improved algorithm are used to optimize the parameters of FIR digital filter in this paper. Firstly, the inertia weight and acceleration factor of particle swarm optimization are discussed. The influence of linear weight and nonlinear weight on the performance of the optimization algorithm is analyzed and other related parameters are discussed. Then the chaos theory is introduced into the nonlinear weight particle swarm optimization. Finally, the FIR digital filter is designed based on the nonlinear weight chaotic particle swarm optimization algorithm. These results show that the FIR digital filter based on the nonlinear weight chaotic particle swarm optimization algorithm has better approximation property and a good performance of convergence.