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Morphological bidirectional associative memories
(Pergamon-elsevier Science LtdOxfordInglaterra, 1999)
Weight vector estimation of circular arrays of antennas using Artificial Neural Networks
(2008-12-01)
This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to ...
Weight vector estimation of circular arrays of antennas using Artificial Neural Networks
(2008-12-01)
This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to ...
A novel approach based on recurrent neural networks applied to nonlinear systems optimization
(Elsevier B.V., 2007-01-01)
This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the ...
Design and analysis of an efficient neural network model for solving nonlinear optimization problems
(Taylor & Francis Ltd, 2005-10-20)
This paper presents an efficient approach based on a recurrent neural network for solving constrained nonlinear optimization. More specifically, a modified Hopfield network is developed, and its internal parameters are ...
A novel approach based on recurrent neural networks applied to nonlinear systems optimization
(Elsevier B.V., 2007-01-01)
This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the ...
Design and analysis of an efficient neural network model for solving nonlinear optimization problems
(Taylor & Francis Ltd, 2005-10-20)
This paper presents an efficient approach based on a recurrent neural network for solving constrained nonlinear optimization. More specifically, a modified Hopfield network is developed, and its internal parameters are ...
Forecasting gold price changes: Rolling and recursive neural network models
(2008)
This paper analyzes recursive and rolling neural network models to forecast one-step-ahead sign variations in gold price. Different combinations of techniques and sample sizes are studied for feed forward and ward neural ...
Compressing arrays of classifiers using Volterra-Neural Network: application to face recognition
(Springer, 2013-07)
Model compression is required when large models are used, for example, for a classification task, but there are transmission, space, time or computing constraints that have to be fulfilled. Multilayer Perceptron (MLP) ...