Perceptrons for photon-limited image classification

Marek Elbaum; Mark Syrkin

doi:10.1117/12.139999

16 September 1992 Perceptrons for photon-limited image classification

Marek Elbaum, Mark Syrkin

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.139999
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

Perceptron learning for the Bayesian classification problem has been analyzed in the framework of Markov diffusion under the influence of competing stochastic forces. The analytic solution for the one-layer architecture yields an immediate relationship between the statistics of the input signal and the weight configuration built by the Perceptron. The computer simulation of the Perceptron learning classification of image-like patterns governed by the Poisson distribution demonstrates a dependence of the learning dynamics on the number of layers and the size of the training data set.

Citation Download Citation

Marek Elbaum and Mark Syrkin "Perceptrons for photon-limited image classification", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.139999

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