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TNN
2010
168views Management» more  TNN 2010»
14 years 11 months ago
On the selection of weight decay parameter for faulty networks
The weight-decay technique is an effective approach to handle overfitting and weight fault. For fault-free networks, without an appropriate value of decay parameter, the trained ne...
Andrew Chi-Sing Leung, Hongjiang Wang, John Sum
177
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TNN
2010
173views Management» more  TNN 2010»
14 years 11 months ago
Global synchronization for discrete-time stochastic complex networks with randomly occurred nonlinearities and mixed time delays
Abstract--In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discretetime stochastic complex networks with randomly occurr...
Zidong Wang, Yao Wang, Yurong Liu
186
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TNN
2010
234views Management» more  TNN 2010»
14 years 11 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
142
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TNN
2010
147views Management» more  TNN 2010»
14 years 11 months ago
Theoretical Model for Mesoscopic-Level Scale-Free Self-Organization of Functional Brain Networks
In this paper we provide theoretical and numerical analysis of a geometric activity flow network model which is aimed at explaining mathematically the scale-free functional graph s...
J. Piersa, Filip Piekniewski, Tomasz Schreiber
TNN
2010
176views Management» more  TNN 2010»
14 years 11 months ago
On the weight convergence of Elman networks
Abstract--An Elman network (EN) can be viewed as a feedforward (FF) neural network with an additional set of inputs from the context layer (feedback from the hidden layer). Therefo...
Qing Song
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