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Chinese Character Recognition Method Based on Multi-features and Parallel Neural Network Computation

机译:基于多特征和并行神经网络计算的汉字识别方法

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Based on neural network with favorable adaptability to handwritten Chinese character multi-features, in this paper a new method is proposed, using existing multi-features as inputs to structure multi neural network recognition subsystems and these subsystems are integrated with parallel connection mode. The integrated system has the lowest false recognition rate. When using traditional von Neumann architecture computer to implement this system, the system response time is longer as a result of serial computation. This paper introduces a kind of parallel computation method of using pc cluster to implement multi subsystems. It can reduce effectively recognition system's response time.
机译:基于神经网络具有良好适应性的汉字多特征,在本文中,提出了一种新方法,使用现有的多个功能作为结构的输入来实现多神经网络识别子系统,这些子系统与并行连接模式集成。集成系统具有最低的虚假识别率。当使用传统的von neumann架构计算机实现该系统时,由于串行计算的结果,系统响应时间更长。本文介绍了一种使用PC集群实现多子系统的并行计算方法。它可以减少有效识别系统的响应时间。

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