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Speech Recognition with TDNN(Time delay neural network)
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用matlab编写BP神经网络实现数据信号分类，本例为语音信号分类-BP neural network with matlab write data signal classification, classification of speech signal in this case
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0案例分析\MATLAB神经网络30个案例分析\源程序\案例1 BP神经网络的数据分类-语音特征信号分类-0 Case Study \ MATLAB neural network analysis of 30 cases \ source \ Case 1 BP neural network data classification- voice characteristic signal classification
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使用Matlab AR模型的LPC函数来做特征值提取。传统方法中LPC一般用来做语音处理。这里每100个数据来做LPC，用获得的N阶参数来作为振动信号的特征值。这样10000个样本可以获得100个特征值样本集。用这些样本集可以做神经网络分类-Matlab AR model LPC function to do eigenvalue extraction. Conventional method LPC generally used for voice processing. Do LPC, wh
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基于matlab的bp神经网络学习算法用于数据的分类--主要针对语音信号进行分类。本案例中选举了民歌、古筝、摇滚和流行音乐四类不同类型，用bp神经网络实现对这四类音乐的有效分类(Based on matlab bp neural network learning algorithm for data classification - mainly for voice signal classification. In this case, four different types of folk
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