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IEICET
2006
60views more  IEICET 2006»
13 years 4 months ago
Temporal Sequences of Patterns with an Inverse Function Delayed Neural Network
A network based on the Inverse Function Delayed (ID) model, which can recall a temporal sequence of patterns, is proposed. The classical problem, that the network is forced to make...
Johan Sveholm, Yoshihiro Hayakawa, Koji Nakajima
CONNECTION
2006
172views more  CONNECTION 2006»
13 years 4 months ago
Temporal sequence detection with spiking neurons: towards recognizing robot language instructions
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
Christo Panchev, Stefan Wermter
SP
2008
IEEE
159views Security Privacy» more  SP 2008»
13 years 4 months ago
Inferring neuronal network connectivity from spike data: A temporal data mining approach
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...
FLAIRS
2003
13 years 5 months ago
Learning Opening Strategy in the Game of Go
In this paper, we present an experimental methodology and results for a machine learning approach to learning opening strategy in the game of Go, a game for which the best compute...
Timothy Huang, Graeme Connell, Bryan McQuade
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...