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Multiple Classes Random Neural Network Model and Color Pattern Recognition Problems

May 31, 2017 | Autor: Jose Aguilar | Categoría: Artificial Intelligence, Image Processing, Signal Processing, Pattern Recognition, Neural Networks, Neural Network, Probability, Recurrent Neural Networks, Image recognition, Color Image, Gradient Descent, Adaptive Thresholding, Pixel, Nonlinear Equations, Neural Network, Probability, Recurrent Neural Networks, Image recognition, Color Image, Gradient Descent, Adaptive Thresholding, Pixel, Nonlinear Equations
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Descripción

The purpose of the paper is to describe the use of the multiple classes random neural network model to learn patterns having different colors. We propose a learning algorithm for the recognition of color patterns based upon the nonlinear equations of the multiple classes random neural network model using gradient descent of a quadratic error function. In addition, we propose a progressive retrieval process with adaptive threshold value
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