Accuracy and Performance Evaluation in the Genetic Optimization of Nonlinear Systems for Active Noise Control
Accuracy and Performance Evaluation in the Genetic Optimization of Nonlinear Systems for Active Noise Control
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DOI：
10.1109/tim.2007.899911
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发表时间：
2007-07
影响因子：
5.6
通讯作者：
F. Russo;G. Sicuranza
中科院分区：
文献类型：
--
作者：
F. Russo;G. Sicuranza
研究了基于沃尔泰拉滤波器的非线性有源噪声控制系统的遗传优化性能。虽然标准的过滤-X算法可能会收敛到局部最小值，遗传算法（GA）可以有效地处理这个问题。此外，这类算法不需要识别次要路径。这是所提出的方法的一个关键优势。计算机仿真表明，即使在次级路径存在非线性的情况下，简单的遗传算法也能找到满意的解，其结果比线性技术和基于经典LMS算法的非线性系统更精确。
This paper investigates the performance of genetic optimization in a nonlinear system for active noise control based on Volterra filters. While standard Filtered-X algorithms may converge to local minima, genetic algorithms (GAs) may handle this problem efficiently. In addition, this class of algorithms does not require the identification of the secondary paths. This is a key advantage of the proposed approach. Computer simulations show that a simple GA is able to find satisfactory solutions even in the presence of nonlinearities in the secondary path. The results are more accurate than using the linear techniques and the nonlinear systems based on classical LMS algorithms.