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A neuron-inspired fuzzy relation model of dynamic systems and its learning algorithms

机译:神经元启发的动态系统模糊关系模型及其学习算法

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In view of fuzzy sets and their operations, three kinds of logic neurons, i.e., AND, OR and AND/OR neurons, are present in this paper. And those neurons can be classified into two types: weighted and relational. Using AND, OR and AND/OR neurons, a fuzzy relational model for dynamic system is provided as well as its learning algorithms. By a simple example, the soundness and the learning capability of the algorithms are verified.
机译:鉴于模糊集及其操作,本文提出了三种逻辑神经元,即AND,OR和AND / OR神经元。这些神经元可以分为两种类型:加权的和相关的。使用AND,OR和AND / OR神经元,提供了动态系统的模糊关系模型及其学习算法。通过一个简单的例子,验证了算法的稳健性和学习能力。

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