Chang Wei-Der
Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan.
Comput Intell Neurosci. 2015;2015:638068. doi: 10.1155/2015/638068. Epub 2015 Aug 3.
This paper develops a new design scheme for the phase response of an all-pass recursive digital filter. A variant of particle swarm optimization (PSO) algorithm will be utilized for solving this kind of filter design problem. It is here called the modified PSO (MPSO) algorithm in which another adjusting factor is more introduced in the velocity updating formula of the algorithm in order to improve the searching ability. In the proposed method, all of the designed filter coefficients are firstly collected to be a parameter vector and this vector is regarded as a particle of the algorithm. The MPSO with a modified velocity formula will force all particles into moving toward the optimal or near optimal solution by minimizing some defined objective function of the optimization problem. To show the effectiveness of the proposed method, two different kinds of linear phase response design examples are illustrated and the general PSO algorithm is compared as well. The obtained results show that the MPSO is superior to the general PSO for the phase response design of digital recursive all-pass filter.
本文针对全通递归数字滤波器的相位响应提出了一种新的设计方案。将采用粒子群优化(PSO)算法的一种变体来解决此类滤波器设计问题。这里将其称为改进粒子群优化(MPSO)算法,该算法在速度更新公式中引入了另一个调整因子,以提高搜索能力。在所提出的方法中,首先将所有设计的滤波器系数收集为一个参数向量,并将该向量视为算法的一个粒子。具有修改后速度公式的MPSO将通过最小化优化问题的一些定义目标函数,迫使所有粒子朝着最优或接近最优解移动。为了说明所提方法的有效性,给出了两种不同线性相位响应设计示例,并与一般PSO算法进行了比较。所得结果表明,在数字递归全通滤波器的相位响应设计方面,MPSO优于一般PSO。