代数模糊神经网络的自适应梯度算法

1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI:10.1109/ISNFS.1996.603837

H. Teodorescu, D. Arotaritei, E. González, A. Mendana

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引用次数: 2

摘要

针对具有模糊权重的代数模糊神经网络，提出了一种基于梯度技术的学习算法。模糊权重可以是三角形模糊数(通常是非对称的)，也可以是梯形模糊数。该网络能够将三角(梯形)模糊数向量映射到任何其他三角(梯形)模糊数向量。

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Adapted gradient algorithm for algebraic fuzzy neural networks

A learning algorithm based on a gradient technique is introduced for the algebraic fuzzy neural network with fuzzy weights. The fuzzy weights can be triangular fuzzy numbers (usually nonsymmetric), or trapezoidal fuzzy numbers. The network is able to map a vector of triangular (trapezoidal) fuzzy numbers into any other vector of triangular (trapezoidal) fuzzy numbers.

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1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report

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