Design of Linear Phase High Pass FIR Filter using Weight Improved Particle Swarm Optimization

被引:0
作者
Yousif, Adel Jalal [1 ]
Ahmed, Ghazwan Jabbar [1 ]
Abbood, Ali Subhi [1 ]
机构
[1] Univ Diyala, Elect Comp Ctr, Diyala, Iraq
关键词
Finite impulse response filter; evolutionary optimization; particle swarm optimization; fitness function; genetic algorithm; high pass filter; impulse response;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The design of Finite Impulse Response (FIR) digital filter involves multi-parameter optimization, while the traditional gradient-based methods are not effective enough for precise design. The aim of this paper is to present a method of designing 24th order high pass FIR filter using an evolutionary heuristic search technique called Weight Improved Particle Swarm Optimization (WIPSO). A new function of the weight parameters is constructed for obtaining a better optimal solution with faster computation. The performance of the proposed algorithm is compared with two other search optimization algorithms namely standard Genetic Algorithm (GA) and conventional Particle Swarm Optimization (PSO). The simulation results show that the proposed WIPSO algorithm is better than GA and PSO in terms of the magnitude response accuracy and the convergence speed for the design of 24th order high pass FIR filter.
引用
收藏
页码:270 / 275
页数:6
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