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HIS
2004
13 years 8 months ago
Q'tron Neural Networks for Constraint Satisfaction
This paper proposes the methods to solve the constraint satisfaction problems (CSPs) using Q'tron neural networks (NNs). A Q'tron NN is local-minima free if it is built ...
Tai-Wen Yue, Mei-Ching Chen
TNN
2010
121views Management» more  TNN 2010»
13 years 1 months ago
Foundations of implementing the competitive layer model by Lotka-Volterra recurrent neural networks
The competitive layer model (CLM) can be described by an optimization problem. The problem can be further formulated by an energy function, called the CLM energy function, in the s...
Zhang Yi
IJCNN
2006
IEEE
14 years 22 days ago
Improvement of an Artificial Neural Network Model using Min-Max Preprocessing for the Prediction of Wave-induced Seabed Liquefac
—In the past decade, artificial neural networks (ANNs) have been widely applied to the engineering problems with a complicated system. ANNs are becoming an important alternative ...
Deaho Cha, Michael Blumenstein, Hong Zhang, Dong-S...
COR
2007
134views more  COR 2007»
13 years 6 months ago
Portfolio selection using neural networks
In this paper we apply a heuristic method based on artificial neural networks (NN) in order to trace out the efficient frontier associated to the portfolio selection problem. We...
Alberto Fernández, Sergio Gómez
VLSISP
2002
114views more  VLSISP 2002»
13 years 6 months ago
Image processing using cellular neural networks based on multi-valued and universal binary neurons
Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an a...
Igor N. Aizenberg, Constantine Butakoff