基于联想存储级联WTA模型的旋转不变识别

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提出一种多目标旋转不变分类识别的新方法。其基本思想是多对一异联想存储模型,为便于光学实现、充分利用系统的时间、空间带宽积,采用了全单极(输入模式和权重均为单极)形成,并对权重进行了二值化截取。一个分布阈值用来克服单极联想存储模型0,1状态分布几率不等时存储容量急剧下降的缺点,同时通过巧妙地选取目标所对应的异联想码将异联想模型和WTA模型有机地结合起来,提高了整个系统的存储容量和容错性。本文给出了计算机仿真模拟及一个光电混合系统的实验结果。
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