Binary neural systems: combining weighted and weightless properties

I. Aleksander, T. Clarke, A. D. P. Braga
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引用次数: 8

Abstract

A neural function is developed that combines the characteristics of weightless and weighted binary neurons. A new combined generalisation algorithm is presented and applied to a neural state machine which is capable of learning to respond to sequences of inputs. The difficulty with such tasks lies in learning appropriate internal state assignments. A particular ‘iconic’ method of solving this problem is discussed. The analysis includes a discussion of implementational issues.
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二元神经系统:结合加权和无权重特性
提出了一种结合无权重和加权二值神经元特性的神经函数。提出了一种新的组合泛化算法,并将其应用于能够学习响应输入序列的神经状态机。这类任务的难点在于学习适当的内部状态分配。讨论了解决这一问题的一种特殊的“图示”方法。分析包括对实施问题的讨论。
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