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首页> 外文期刊>BioTechnology: An Indian Journal >Study of computer digital signal processing network based on the genetic algorithm
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Study of computer digital signal processing network based on the genetic algorithm

机译：基于遗传算法的计算机数字信号处理网络研究

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With the extensive application of computer technology in all areas of society, the computer has become indispensable to people's lives, an important part. Computer voice digital signal is more due to its simple, direct, and easy to be accepted into many areas of the characteristics of human society. In the popularization of computer technology, the popularity of the trend, subject to a number of computer-aided voice processing software for real-time signal processing is based on an important development direction of generalpurpose computer signal processing simulation system. This article focuses on the genetic algorithm to improve computer assisted voice digital signal processing technology, focusing on the effect of genetic algorithms in terms of speaker recognition, proposed a set of related technologies using genetic algorithm to improve computer-aided optimization of voice processing solutions. One can easily LBG algorithm for speech processing plays an important role in vector quantization techniques used in the design process codebook into local optimum problem, will produce genetic algorithm (GA) and its combination of GA-LBG algorithm;Second, for poorly performing computer-aided speech processing problems play a very important role in neural network RBF network obtained in the clustering process, combined with improved adaptive genetic algorithm to optimize the design of the network training algorithms. Examples of the computer-aided speaker recognition by voice processing applications through improved genetic algorithm LBG algorithm and RBF neural networks were trained and identified.Experimental results show a good effect on genetic algorithm optimized generated.
机译：随着计算机技术在社会各个领域的广泛应用，计算机已成为人们生活中不可缺少的重要组成部分。计算机语音数字信号更多地是由于其简单，直接和易于被人类社会特征的许多领域接受。在计算机技术的普及，普及的趋势下，受众多计算机辅助语音处理软件进行实时信号处理的基础是通用计算机信号处理仿真系统的重要发展方向。本文重点介绍了遗传算法来改进计算机辅助语音数字信号处理技术，着眼于遗传算法在说话人识别方面的效果，提出了一套利用遗传算法改进计算机辅助语音处理解决方案的相关技术。一种可以轻松地将LBG算法用于语音处理的问题，在设计过程码本中使用的矢量量化技术中将其转化为局部最优问题，将产生遗传算法（GA）及其GA-LBG算法的结合;其次，对于性能较差的计算机，辅助语音处理问题在聚类过程中获得的神经网络RBF网络中起着非常重要的作用，并结合改进的自适应遗传算法来优化网络训练算法的设计。通过改进的遗传算法LBG算法和RBF神经网络进行语音处理应用的计算机辅助说话人识别的实例进行了训练和识别。

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