Correlation Discriminator of Images in the Class of Fast Neural Networks

A. Dorogov
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引用次数: 1

Abstract

The paper presents methods for constructing topology and parametric training of fast neural networks (FNN) for tasks of image correlation processing. A mathematical model of the two dimension FNN is described. The connection of fast algorithms with self-similar structures is noted. A method of multiplicative representation of arbitrary discrete images is shown. Algorithms for constructing the FNN topology and training for implementing a correlation image discriminator are proposed.
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一类快速神经网络中图像的相关鉴别器
本文介绍了用于图像相关处理任务的快速神经网络(FNN)的拓扑构造和参数训练方法。描述了二维模糊神经网络的数学模型。指出了快速算法与自相似结构的联系。给出了一种任意离散图像的乘法表示方法。提出了构建FNN拓扑的算法和实现相关图像鉴别器的训练算法。
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