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Optimizing method for analog circuit design using adaptive immune genetic algorithm

机译:基于自适应免疫遗传算法的模拟电路设计优化方法

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The design of an analog circuit is so complex that much time is required. To improve the speed and efficiency of evolutionary hardware design, this paper presented an adaptive immune genetic Algorithm (AIGA). The optimization of the analog circuit is the optimization of multi-dimensional parameters, and the trade-off of all parameters. The genetic algorithm is suitable for the optimization of the multidimensional parameters and the immune algorithm is suitable for the improvement of diversity. So AIGA can improve the searching ability, adaptability and the convergence speed. As an example, the optimization of parameters of a low-pass filter is presented. From simulation results, we confirm that the proposed method is suitable for the optimizing of the analog circuit.
机译:模拟电路的设计如此复杂,需要很多时间。为了提高进化硬件设计的速度和效率,本文提出了一种自适应免疫遗传算法(AIGA)。模拟电路的优化是优化多维参数,以及所有参数的权衡。遗传算法适用于多维参数的优化,免疫算法适用于改善多样性。因此,AIGA可以提高搜索能力,适应性和收敛速度。作为示例,呈现了低通滤波器的参数的优化。从仿真结果中,我们确认所提出的方法适用于优化模拟电路。

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