Pii: S0893-6080(96)00128-1
نویسنده
چکیده
Real-codedgenetic algorithms on a parallel architecture are applied to optimize the synaptic couplings of a Cellular Neural Network for specific greyscale image processing tasks. Using supervised learning information in the jitnessfinction, we propose the Genetic Algorithm as a general training methodfor Cellular Neural Networks. 01997 Elsevier Science Ltd. Keywords-Cellular neuralnetworks,Geneticalgorithms,Supervisedlearning,Imageprocessing.
منابع مشابه
Stochastic resonance in noisy threshold neurons
Stochastic resonance occurs when noise improves how a nonlinear system performs. This paper presents two general stochastic-resonance theorems for threshold neurons that process noisy Bernoulli input sequences. The performance measure is Shannon mutual information. The theorems show that small amounts of independent additive noise can increase the mutual information of threshold neurons if the ...
متن کاملVarieties of Helmholtz Machine
The Helmholtz machine is a new unsupervised learning architecture that uses top-down connections to build probability density models of input and bottom-up connections to build inverses to those models. The wake-sleep learning algorithm for the machine involves just the purely local delta rule. This paper suggests a number of different varieties of Helmholtz machines, each with its own strength...
متن کاملAn Efficient Mapping of Fuzzy ART onto a Neural Architecture
A novel mapping of the Fuzzy ART algorithm onto a neural network architecture is described. The architecture does not utilize bi-directional synapses, weight transport, or weight duplication, and requires one fewer layer of processing elements than the architecture originally proposed by Carpenter, Grossberg, & Rosen (1991a). In the new architecture, execution of the algorithm takes constant ti...
متن کاملPii: S0893-6080(00)00062-9
This article gives an overview of the different functional brain imaging methods, the kinds of questions these methods try to address and some of the questions associated with functional neuroimaging data for which neural modeling must be employed to provide reasonable answers. q 2000 Published by Elsevier Science Ltd.
متن کاملPii: S0893-6080(99)00042-8
This paper presents a theoretical analysis on the asymptotic memory capacity of the generalized Hopfield network. The perceptron learning scheme is proposed to store sample patterns as the stable states in a generalized Hopfield network. We have obtained that n 2 1 and 2n are a lower and an upper bound of the asymptotic memory capacity of the network of n neurons, respectively, which shows th...
متن کامل