A neural network classifier based on HMM framework was proposed.It can be used to identify timevarying signal, which an ordinary neural network lacks of, and can stress the differences of different signals. Evolutionary learning of the neural network weights using genetic algorithm solves the problem of falling into local minimum point which BP and Baum Welch algorithmnace. An example of recognizing radar return signal successfully by the neural netwrok was presented.
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周德全 郭耀红.用HM框架下的神经网络分类器识别雷达目标[J].红外与毫米波学报,2001,20(2):107~110]. ZHOU De Quan GUO Yao Hong. RADAR TARGET IDENTIFICATION USING NEURAL NETWORK CLASSIFIER BASED ON HMM FRAMEWORK[J]. J. Infrared Millim. Waves,2001,20(2):107~110.]