| 基于遗传神经网络优化的过程信号盲分离算法 |
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| 引用本文： | 华容.基于遗传神经网络优化的过程信号盲分离算法[J].计算机工程与设计,2007,28(18):4459-4461. |
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| 作者姓名： | 华容 |
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| 作者单位： | 上海应用技术学院机械与自动化工程学院 上海200235 |
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| 摘 要： | 研究一种较新的盲信号神经网络分离(BSS)方法,用于过程信号去噪.由于盲信号分离神经网络存在容易陷入局部极小点、收敛速度慢的缺点,研究采用遗传算法优化盲信号分离神经网络权值的初值,将遗传算法与神经网络(HJNN)结合形成GA-HJNN算法,可迅速得到最佳盲信号分离神经网络的权值矩阵,实现对过程信号的去噪,并通过实验对2种算法进行了比较.
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| 关 键 词： | 遗传算法 神经网络 盲分离 过程信号 去噪 遗传算法 神经网络 网络优化 过程信号 盲分离算法 neural network genetic based signal process algorithm separation 比较 实验 信号去噪 权值矩阵 最佳 结合 初值 网络权值 |
| 文章编号： | 1000-7024（2007）18-4459-03 |
| 修稿时间： | 2006-10-20 |
Blind separation algorithm of process signal based on optimized genetic and neural network |
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| HUA Rong.Blind separation algorithm of process signal based on optimized genetic and neural network[J].Computer Engineering and Design,2007,28(18):4459-4461. |
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| Authors: | HUA Rong |
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| Affiliation: | School of Mechanical and Automation Engineering, Shanghai Institute of Technology, Shanghai 200235, China |
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| Abstract: | One of the main weak-points of the blind separation algorithm of HJNN is that the optimal procedure is easily stacked into the local minimal value and it causes slow convergence. Based on genetic algorithm (GA), GA-HJNN algorithm to optimize the initial value of the weight of HJNN is proposed so as to obtain the optimum weight matrix quickly and realize the demising of the process signal. The comparison between the two algorithms is given with experiment. |
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| Keywords: | genetic algorithm neural network blind separation process signal noise-cancellation |
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