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» A spiking neuron model: applications and learning
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TNN
2008
85views more  TNN 2008»
13 years 4 months ago
Training Spiking Neuronal Networks With Applications in Engineering Tasks
In this paper, spiking neuronal models employing means, variances, and correlations for computation are introduced. We present two approaches in the design of spiking neuronal netw...
Phill Rowcliffe, Jianfeng Feng
BIOADIT
2004
Springer
13 years 10 months ago
A Hardware Implementation of a Network of Functional Spiking Neurons with Hebbian Learning
Abstract. In this paper we present a functional model of a spiking neuron intended for hardware implementation. Some features of biological spiking neuabstracted, while preserving ...
Andres Upegui, Carlos Andrés Peña-Re...
NN
2002
Springer
208views Neural Networks» more  NN 2002»
13 years 4 months ago
A spiking neuron model: applications and learning
This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the mo...
Chris Christodoulou, Guido Bugmann, Trevor G. Clar...
BC
2002
85views more  BC 2002»
13 years 4 months ago
Spike propagation synchronized by temporally asymmetric Hebbian learning
Synchronously spiking neurons have been observed in the cerebral cortex and the hippocampus. In computer models, synchronous spike volleys may be propagated across appropriately co...
Roland E. Suri, Terrence J. Sejnowski
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
13 years 11 months ago
Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
Debprakash Patnaik, Srivatsan Laxman, Naren Ramakr...