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A Boolean Neural Network Controlling Task Sequences in a Noisy Environment

机译:嘈杂环境中控制任务序列的布尔神经网络

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The classical exclusive-or problem and many others like it cannot be performed with networks without hidden units, with which they create their own internal representation of the input patterns. The idea to use multi-layered network for solving that kine of problems has been successful, but it requires to find powerful learning rules for networks with hidden units, that are also very simple guaranteed learning rules. We propose a quite general solution for implementing a Hebbian rule into non-layered Boolean neural network, in order to solve that kind of problems. We aslo present some experimental results.
机译:经典的“异或”问题和许多其他类似的问题不能在没有隐藏单元的网络上执行,因为隐藏单元可以使用它们自己创建输入模式的内部表示。使用多层网络解决问题的想法已经成功,但是它需要为具有隐藏单元的网络找到强大的学习规则,这也是非常简单的保证学习规则。为了解决这类问题,我们提出了一种将Hebbian规则实施到非分层布尔神经网络中的通用解决方案。我们还提出了一些实验结果。

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