时序模式的一种神经网络分类方法

AN NN CLASSIFICATION METHOD FOR THE \=TIMESEQUENCE PATTERN

时序模式是指其特征空间分布在时间轴上的一种模式，如语音信号、雷达信号等．文中提出了一种改进的递归神经网方法——时间标签递归神经网方法，以此来对时序模式进行分类，克服了传统方法的缺点，取得了较好的分类效果．初步的实验结果不仅证明了时间标签递归神经网方法对时序模式的很好的分类能力，而且证明了时间标签对于时序模式分类的重要性．

The time\|sequence pattern is a pattern,whose characteristic space is distributed on the time\|axis,such as speech signal,radar signal,etc..Presented in the paper is an improved recurrent neural network methodthe time\|tag recurrent neural network (TTRNN) method,to classify the time\|sequence patterns directly,which overcomes the drawbacks of the traditional method,and a good result is achieved.The preliminary experiment not only proves the good performance of the TTRNN method in the clasification of the time\|sequence patterns,but also proves the importance of time\|tag in the classification of the time\|sequence patterns.