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GA遗传算法解决TSP问题

于 2021-04-23 发布

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说明： GA遗传算法解决TSP问题，旨在以遗传算法解决城市路径规划最优问题。(The purpose of solving TSP problem with GA is to solve the optimal problem of urban path planning with GA.)

文件列表：

GA遗传算法解决TSP问题, 0 , 2021-04-17
GA遗传算法解决TSP问题\cross.m, 970 , 2020-05-10
GA遗传算法解决TSP问题\exchange.m, 75 , 2020-05-10
GA遗传算法解决TSP问题\fit.m, 176 , 2020-05-10
GA遗传算法解决TSP问题\main.m, 3489 , 2020-05-10
GA遗传算法解决TSP问题\mutation.m, 242 , 2020-05-10
GA遗传算法解决TSP问题\myLength.m, 368 , 2020-05-10
GA遗传算法解决TSP问题\plot_route.m, 467 , 2020-05-10
GA遗传算法解决TSP问题\reverse.m, 533 , 2020-05-10

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pll
设计的软件锁相环的例子，自己写的，根据原理编的(PLL design example of software that he wrote, according to the principle for the)

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2008-06-25 21:09:47下载

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研究表明超高斯分布更加贴近语音信号的实际分布，然而语音信号很难用单一的概率密度函数准确描述，针对这一情况，提出了一种用超高斯混合模型对语音信号幅度谱建模的新方法，并推导了基于此模型的幅度谱最小均方误差估的估计式。仿真结果表明：与传统的短时谱估计算法相比，该算法不仅能够进一步提高增强语音的信噪比，而且可以有效减小增强语音的失真度，提高增强语音的主观感知质量。 (Recent research indicates that the speech spectral amplitude distributions could be fairly described with super-Gaussian probability density function. However, the complexity of speech signal determines that the distribution statistics ofspeech signal could not be well described by single simple function. Thus a super-Gaussian mixture model for speech spectral amplitude is proposed, and with this model, a minimum mean-square error (MMSE) estimator for speech signals spectral amplitude is derived. The simulation results show that this algorithm based on Gaussian and super-Gaussian speech model could achieve better noise suppression and lower speech distortion as compared with the conventional short-time spectral amplitude estimation algorithm. )

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GA遗传算法解决TSP问题

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