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Study on Signal Fitting Based on Simulated Annealing and Soft Function Basis

机译:基于模拟退火和软函数基的信号拟合研究

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摘要

Based on simulated annealing algorithm (SAA) and soft function basis (SFB), algorithm of dealing with one dimensional signal fitting by means of neural network is presented. The key point is that we employ SAA to get new states with fixed probability in the process of signal fitting. The combination of SFB and SAA and the selection of soft SFB are analyzed in emphasis. Simulation shows that the algorithm works well for signal fitting. But there are undoubtedly some drawbacks existing in the present model. We will do further research in the further study.
机译:基于模拟退火算法(SAA)和软函数基础(SFB),提出了一种基于神经网络的一维信号拟合算法。关键是我们在信号拟合过程中采用SAA以固定的概率获得新状态。重点分析了SFB和SAA的组合以及软SFB的选择。仿真表明,该算法在信号拟合中效果很好。但是,毫无疑问,当前模型存在一些缺陷。我们将在进一步的研究中做进一步的研究。

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