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A handwritten character recognition algorithm based on artificial immune

机译:基于人工免疫的手写字符识别算法

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Handwritten character recognition is an important research and application area on pattern recognition theory, which plays an important role on realizing automation of inputting character at all cases. In order to improve the rate of character recognition and decrease the time of recognition training, referencing to immune biological principle, a handwritten character recognition algorithm based on artificial immune is proposed. The antigen and memory cell in the artificial immune system are described. The equations of clone selection principle and of evolving memory cell are established. Finally, the process of character recognition is given. The experiment uses the well-know character set providing by F.Prat from UCI. The simulation results show that the method has faster speed and higher accuracy than the traditional handwritten recognition based on neural network. The algorithm steals the merit of self-adaptive learning, and immune memory in the biology immune system, which can also be applied to abnormity detection and pattern recognition.
机译:手写字符识别是模式识别理论的重要研究和应用领域,对于在所有情况下实现字符输入的自动化都具有重要作用。为了提高字符识别率,减少识别训练时间,结合免疫生物学原理,提出了一种基于人工免疫的手写字符识别算法。描述了人工免疫系统中的抗原和记忆细胞。建立了克隆选择原理和进化记忆单元的方程式。最后给出了字符识别的过程。实验使用了UCI的F.Prat提供的知名字符集。仿真结果表明,该方法比传统的基于神经网络的手写识别具有更快的速度和更高的准确性。该算法窃取了自适应学习和生物免疫系统中的免疫记忆的优点,也可以应用于异常检测和模式识别。

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