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10 years 3 months ago
Nguyen-Widrow and other Neural Network Weight/Threshold Initialization Methods
Neural networks learn by adjusting numeric values called weights and thresholds. A weight specifies how strong of a connection exists between two neurons. A threshold is a value,...
Jeff Heaton
NCA
2006
IEEE
9 years 8 months ago
Evolutionary training of hardware realizable multilayer perceptrons
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...
Vassilis P. Plagianakos, George D. Magoulas, Micha...
JMLR
2006
389views more  JMLR 2006»
9 years 8 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
HIS
2001
9 years 9 months ago
Global Optimisation of Neural Networks Using a Deterministic Hybrid Approach
Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural...
Gleb Beliakov, Ajith Abraham
AINA
2010
IEEE
9 years 11 months ago
Mnesic Evocation: An Isochron-Based Analysis
—Mnesic evocation occurs under the action of a stimulus. A successful evocation is observed as the overrun of a certain threshold of the neuronal activity followed by a medical i...
Hedi Ben Amor, Jacques Demongeot, Nicolas Glade
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