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NIPS
2000
13 years 9 months ago
Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks
It has long been known that lateral inhibition in neural networks can lead to a winner-take-all competition, so that only a single neuron is active at a steady state. Here we show...
Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian...
BC
2006
63views more  BC 2006»
13 years 7 months ago
Dynamic neural field with local inhibition
Abstract A lateral-inhibition type neural field model with restricted connections is presented here and represents an experimental extension of the Continuum Neural Field Theory (C...
Nicolas P. Rougier
IJCNN
2000
IEEE
14 years 6 hour ago
Regression Analysis for Rival Penalized Competitive Learning Binary Tree
The main aim of this paper is to develop a suitable regression analysis model for describing the relationship between the index efficiency and the parameters of the Rival Penaliz...
Xuequn Li, Irwin King
HYBRID
1998
Springer
13 years 12 months ago
High Order Eigentensors as Symbolic Rules in Competitive Learning
We discuss properties of high order neurons in competitive learning. In such neurons, geometric shapes replace the role of classic `point' neurons in neural networks. Complex ...
Hod Lipson, Hava T. Siegelmann
TSMC
2002
129views more  TSMC 2002»
13 years 7 months ago
A distributed robotic control system based on a temporal self-organizing neural network
A distributed robot control system is proposed based on a temporal self-organizing neural network, called competitive and temporal Hebbian (CTH) network. The CTH network can learn ...
Guilherme De A. Barreto, Aluizio F. R. Araú...