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Genetic Algorithm for Restricted Maximum k-Satisfiability in the Hopfield Network
The restricted Maximum k-Satisfiability MAX- kSAT is an enhanced Boolean satisfiability counterpart that has attracted numerous amount of research. Genetic algorithm has been the prominent optimization heuristic algorithm ...
Synaptic compensation on Hopfield network: implications for memory rehabilitation
(SPRINGER, 2011)
The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons ...
Robust Artificial Immune System in the Hopfield network for Maximum k-Satisfiability
Artificial Immune System (AIS) algorithm is a novel and vibrant computational paradigm, enthused by the biological immune system. Over the last few years, the artificial immune system has been sprouting to solve numerous ...
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 ...
A barrier method for constrained nonlinear optimization using a modified Hopfield network
(2001-01-01)
The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel barrier method using artificial neural networks to solve robust parameter ...
A barrier method for constrained nonlinear optimization using a modified Hopfield network
(2001-01-01)
The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel barrier method using artificial neural networks to solve robust parameter ...
An efficient Hopfield network to solve economic dispatch problems with transmission system representation
(Elsevier B.V., 2004-11-01)
Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple ...