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Synthesis Tool Based on Genetic Algorithm for FIR Filters with User-Defined Magnitude Characteristics

机译:基于遗传算法的具有用户定义幅值特征的FIR滤波器综合工具

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This paper presents a method for synthesizing linear-phase FIR filters capable of implementing magnitude characteristics defined arbitrarily by the user through a set of frequency-magnitude points, filters that are optimized with respect to several criteria. The main idea is to approach the filter synthesis as a multi-objective optimization problem, targeting the minimization of both the peak magnitude and the total squared errors of the resulting magnitude characteristics, as well as implementation-related requirements such as the reduction of the filter length. The optimization procedure uses a genetic algorithm tailored to this application; it employs a novel encoding scheme for the filter chromosome and an efficient fitness function, based on only two well-chosen constraints. Several design examples are presented: first, optimized synthesis of FIR filters with magnitude characteristics that match given (arbitrary) human audiograms, and second, synthesis of filters defined by parameters related to their pass- and stop-bands. The results yielded by the proposed method compare well with filters synthesized by means of previously reported methods and an industry-standard MATLAB tool.
机译:本文提出了一种合成线性相位FIR滤波器的方法,该滤波器能够实现用户通过一组频率-幅度点来任意定义的幅度特性,这些滤波器针对多个标准进行了优化。主要思想是将滤波器综合作为多目标优化问题进行处理,目标是使峰值幅度和所产生幅度特征的总平方误差最小化,以及与实现相关的要求,例如减少滤波器长度。优化过程使用了针对该应用量身定制的遗传算法。它仅基于两个精心选择的约束条件,对过滤器染色体采用了新颖的编码方案,并具有有效的适应度函数。给出了几个设计示例:首先,优化的FIR滤波器的合成,其幅度特性与给定的(任意)人类听力图相匹配;其次,合成由与通带和阻带有关的参数定义的滤波器。所提出的方法产生的结果与通过先前报道的方法和行业标准的MATLAB工具合成的滤波器进行了很好的比较。

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