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» Optimizing number of hidden neurons in neural networks
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JCNS
2010
121views more  JCNS 2010»
13 years 2 months ago
Pattern orthogonalization via channel decorrelation by adaptive networks
The early processing of sensory information by neuronal circuits often includes a reshaping of activity patterns that may facilitate the further processing of stimulus representat...
Stuart D. Wick, Martin T. Wiechert, Rainer W. Frie...
NPL
1998
133views more  NPL 1998»
13 years 7 months ago
Parallel Coarse Grain Computing of Boltzmann Machines
Abstract. The resolution of combinatorial optimization problems can greatly benefit from the parallel and distributed processing which is characteristic of neural network paradigm...
Julio Ortega, Ignacio Rojas, Antonio F. Día...
IJON
2008
177views more  IJON 2008»
13 years 8 months ago
An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem
In this paper, an approach to solving the classical Traveling Salesman Problem (TSP) using a recurrent network of linear threshold (LT) neurons is proposed. It maps the classical ...
Eu Jin Teoh, Kay Chen Tan, H. J. Tang, Cheng Xiang...
ICANN
2007
Springer
14 years 2 months ago
SpikeStream: A Fast and Flexible Simulator of Spiking Neural Networks
SpikeStream is a new simulator of biologically structured spiking neural networks that can be used to edit, display and simulate up to 100,000 neurons. This simulator uses a combin...
David Gamez
NIPS
2007
13 years 9 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...