Generalizing Operations of Binary Autoassociative Morphological Memories Using Fuzzy Set Theory

被引：0

作者：

Peter Sussner

机构：

[1] State University of Campinas,Institute of Mathematics, Statistics, and Scientific Computing

来源：

Journal of Mathematical Imaging and Vision | 2003年 / 19卷

关键词：

morphological neural network; associative memory; morphological associative memory; image algebra; fuzzy set theory;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Morphological neural networks (MNNs) are a class of artificial neural networks whose operations can be expressed in the mathematical theory of minimax algebra. In a morphological neural net, the usual sum of weighted inputs is replaced by a maximum or minimum of weighted inputs (in this context, the weighting is performed by summing the weight and the input). We speak of a max product, a min product respectively.

引用

页码：81 / 93

页数：12

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