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TIT
2002
89views more  TIT 2002»
15 years 3 months ago
Comparison of worst case errors in linear and neural network approximation
Sets of multivariable functions are described for which worst case errors in linear approximation are larger than those in approximation by neural networks. A theoretical framework...
Vera Kurková, Marcello Sanguineti
114
Voted
NN
1998
Springer
15 years 3 months ago
Statistical estimation of the number of hidden units for feedforward neural networks
The number of required hidden units is statistically estimated for feedforward neural networks that are constructed by adding hidden units one by one. The output error decreases w...
Osamu Fujita
153
Voted
IJON
2008
152views more  IJON 2008»
15 years 2 months ago
Topos: Spiking neural networks for temporal pattern recognition in complex real sounds
This article depicts the approach used to build the Topos application, a simulation of two-wheel robots able to discern real complex sounds. Topos is framed in the nouvelle concep...
Pablo González-Nalda, Blanca Cases
183
Voted
SMC
2010
IEEE
276views Control Systems» more  SMC 2010»
15 years 1 months ago
A Modified Invasive Weed Optimization Algorithm for training of feed- forward Neural Networks
— Invasive Weed Optimization Algorithm IWO) is an ecologically inspired metaheuristic that mimics the process of weeds colonization and distribution and is capable of solving mul...
Ritwik Giri, Aritra Chowdhury, Arnob Ghosh, Swagat...
131
Voted
SIAMADS
2010
145views more  SIAMADS 2010»
14 years 10 months ago
Propagation of Spike Sequences in Neural Networks
Precise spatiotemporal sequences of action potentials are observed in many brain areas and are thought to be involved in the neural processing of sensory stimuli. Here, we examine ...
Arnaud Tonnelier