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» Neural Dynamics with Stochasticity
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NIPS
2008
15 years 7 months ago
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...
ICANN
2010
Springer
15 years 4 months ago
Dynamics and Function of a CA1 Model of the Hippocampus during Theta and Ripples
The hippocampus is known to be involved in spatial learning in rats. Spatial learning involves the encoding and replay of temporally sequenced spatial information. Temporally seque...
Vassilis Cutsuridis, Michael E. Hasselmo
ICTAI
2008
IEEE
16 years 22 days 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
ECAL
2005
Springer
15 years 12 months ago
Measuring Diversity in Populations Employing Cultural Learning in Dynamic Environments
Abstract. This paper examines the effect of cultural learning on a population of neural networks. We compare the genotypic and phenotypic diversity of populations employing only p...
Dara Curran, Colm O'Riordan
MVA
1996
167views Computer Vision» more  MVA 1996»
15 years 7 months ago
Applying a Dynamic Recognition Scheme for Vehicle Recognition in Many Object Traffic Scenes
An adaptive object recognition scheme for image sequences of many object scenes is described. The scheme is applied for t r d c object recognition under ego-motion. The recursive ...
Wlodzimierz Kasprzak, Heinrich Niemann