ANN-based classifier of features produced by computer generated holograms

被引：0

作者：

Cyran, KA ^{[1
]}

Jaroszewicz, LR ^{[1
]}

机构：

[1] Silesian Tech Univ, Inst Comp Sci, Gliwice, Poland

来源：

PROGRAMMABLE DEVICES AND SYSTEMS | 2000年

关键词：

signal processing; neural networks; pattern recognition; classifiers; learning algorithms; optical fibers;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper presents the ANN-based pattern recognition system with computer generated hologram (CGH) used as a feature extractor. Features obtained by standard and optimized CGH are classified using multi layer perceptron network. Experiments with gradient and stochastic learning rules, as well as different hidden layer sizes for this system are presented. The objective in these experiments, were to classify the distortion of quasi-monomode optical fiber from speckle images taken when this distortion occurred. Copyright (C) 2000 IFAC.

引用

页码：99 / 104

页数：6

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