Reconstructing signal from fiber-optic measuring system with non-linear perceptron

Details Reconstructing signal from fiber-optic measuring system with non-linear perceptron Reconstructing signal from fiber-optic measuring system with non-linear perceptron

2001-03-05

arxiv.org/abs/cond-mat/0103092v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

3 pages, Latex, 1 postscript figure

Scientific paper

A computer model of the feed-forward neural network with the hidden layer is developed to reconstruct physical field investigated by the fiber-optic measuring system. The Gaussian distributions of some physical quantity are selected as learning patterns. Neural network is learned by error back-propagation using the conjugate gradient and coordinate descent minimization of deviation. Learned neural network reconstructs the two-dimensional scalar physical field with distribution having one or two Gaussian peaks.

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