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EM-based optimization of microwave circuits using artificial neural networks: the state of the art
(IEEE Trans. Microwave Theory Tech.;52, 2004-01)
Removing Unclassified Hand Tremor Motion from Computer Mouse Input with Neural Networks
An artificial neural network based filter to remove unwanted tremor-induced motion in computer mouse input is presented and tested. A method to efficiently capture appropriate training data is shown to be important in the ...
Shape, connectedness and dynamics in neuronal networks
(Elsevier BVAmsterdam, 2013-11)
The morphology of neurons is directly related to several aspects of the nervous system, including its connectedness, health, development, evolution, dynamics and, ultimately, behavior. Such interplays of the neuronal ...
Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems
(Elsevier B.V., 2011-01-01)
This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. ...
Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems
(Elsevier B.V., 2011-01-01)
This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. ...
Artificial neural network model of discharge lamps in the power quality context
(2013-06-01)
This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of ...
Artificial neural network model of discharge lamps in the power quality context
(2013-06-01)
This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of ...
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 ...