首页> 外国专利> Computer-aided learning of neural networks involves changing cross-links between first and second layers of neurons of neural network based on variable state of neural network which is determined using feature instances and categories

Computer-aided learning of neural networks involves changing cross-links between first and second layers of neurons of neural network based on variable state of neural network which is determined using feature instances and categories

机译:神经网络的计算机辅助学习涉及基于神经网络的可变状态更改神经网络的第一层神经元与第二层神经元之间的交叉链接,该状态是使用特征实例和类别确定的

摘要

The method involves dividing the neurons of a neural network (1) into two interlaced layers (L1,L2). The first layer stores feature instances represented by the input data. The second layer stores majority of categories covering the neurons in the second layer. Each category in second layer is assigned to each feature instance in the first layer. The varying state of the neural network is determined based on the categories with assigned feature instances after entering the input data. The cross-links between first and second layer is changed based on the determined state of the neural network. An independent claim is included for the neural network.
机译:该方法包括将神经网络(1)的神经元分为两个交错层(L1,L2)。第一层存储由输入数据表示的要素实例。第二层存储第二层中覆盖神经元的大多数类别。第二层中的每个类别都分配给第一层中的每个要素实例。输入输入数据后,基于具有指定特征实例的类别确定神经网络的变化状态。基于神经网络的确定状态,可以更改第一层和第二层之间的交叉链接。该神经网络包含独立声明。

著录项

  • 公开/公告号DE102005046747B3

    专利类型

  • 公开/公告日2007-03-01

    原文格式PDF

  • 申请/专利权人 SIEMENS AG;

    申请/专利号DE20051046747

  • 发明设计人 DECO GUSTAVO;STETTER MARTIN;SZABO MIRUNA;

    申请日2005-09-29

  • 分类号G06N3/02;

  • 国家 DE

  • 入库时间 2022-08-21 20:29:46

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