Genetic algorithm approach for the optimization of multiplierless sub-filters generated by the frequency-response masking technique
Genetic algorithm approach for the optimization of multiplierless sub-filters generated by the frequency-response masking technique
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DOI：
10.1109/icecs.2002.1046459
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发表时间：
2002-12
期刊：
影响因子：
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通讯作者：
Y. Yu;Y. Lim
中科院分区：
文献类型：
--
作者：
Y. Yu;Y. Lim
本文采用遗传算法优化由频率响应掩蔽技术（FRM）产生的具有非常尖锐线性相位的FIR数字滤波器的离散系数值。离散系数空间是有符号二次幂（SPT）空间。由于遗传算法同时优化所有子滤波器的系数，它克服了线性优化技术存在的缺点，单独优化子滤波器。如果遗传算法从通过使用非线性联合优化算法获得的连续解开始，则所获得的离散解的总体纹波幅度非常接近于连续解的总体纹波幅度。与通过对连续解的系数值进行四舍五入得到的离散系数滤波器相比，实现了很大的改进。
In this paper, the genetic algorithm (GA) is applied to optimize the discrete coefficient values of very sharp linear phase FIR digital filters generated by the frequency-response masking (FRM) technique. The discrete coefficient space is the signed power-of-two (SPT) space. Since the genetic algorithm optimizes all the sub-filters' coefficients simultaneously, it overcomes the drawback existing in linear optimization technique that optimizes the sub-filters individually. If the genetic algorithm starts from the continuous solution obtained by using a non-linear joint optimization algorithm, the obtained overall ripple magnitude of the discrete solution is very close to that of the continuous solution. Great improvement is achieved compared to the discrete coefficient filters obtained by rounding the coefficient values of the continuous solutions.