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» Neural network ensembles for time series forecasting
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BC
2007
107views more  BC 2007»
14 years 9 months ago
Decoding spike train ensembles: tracking a moving stimulus
We consider the issue of how to read out the information from nonstationary spike train ensembles. Based on the theory of censored data in statistics, we propose a ‘censored’ m...
Enrico Rossoni, Jianfeng Feng
ICTAI
2008
IEEE
15 years 3 months ago
The Performance of Approximating Ordinary Differential Equations by Neural Nets
—The dynamics of many systems are described by ordinary differential equations (ODE). Solving ODEs with standard methods (i.e. numerical integration) needs a high amount of compu...
Josef Fojdl, Rüdiger W. Brause
NN
2007
Springer
267views Neural Networks» more  NN 2007»
14 years 9 months ago
Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
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JCNS
2010
121views more  JCNS 2010»
14 years 4 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...
ISNN
2004
Springer
15 years 2 months ago
Rainfall-Runoff Correlation with Particle Swarm Optimization Algorithm
A reliable correlation between rainfall-runoff enables the local authority to gain more amble time for formulation of appropriate decision making, issuance of an advanced flood for...
Kwok-wing Chau