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A multi-objective covariance matrix adaptation evolutionary strategy based on decomposition for analog circuit design

机译:基于分解的模拟电路设计多目标协方差矩阵自适应进化策略

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Sound localization has been utilized in many fields. For good performance, sound signal obtained from the microphone has to be well filtered and amplified. Although filtering and amplification can be implemented in digital, analog circuit is needed because of sampling aliasing problem and limitation of computational resources in real-time application. The analog circuit consists of several components. Because all of possible combinations cannot be investigated, evolutionary algorithm (EA) is chosen to find promising solution candidates. In the paper, we built a multi-objective covariance adaptation evolutionary strategy based on decomposition to obtain the component values. Through the experimental results, our proposed algorithm showed good performance.
机译:声音本地化已在许多领域中得到利用。为了获得良好的性能,必须对从麦克风获得的声音信号进行良好的滤波和放大。尽管可以在数字中实现滤波和放大,但是由于采样混叠问题和实时应用中计算资源的限制,仍需要模拟电路。模拟电路由几个组件组成。由于无法研究所有可能的组合,因此选择了进化算法(EA)来寻找有前途的解决方案候选者。在本文中,我们基于分解建立了多目标协方差适应进化策略,以获取分量值。通过实验结果,我们提出的算法表现出良好的性能。

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