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» Learning Mappings with Neural Network
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ESANN
2006
15 years 3 months ago
Magnification control for batch neural gas
Neural gas (NG) constitutes a very robust clustering algorithm which can be derived as stochastic gradient descent from a cost function closely connected to the quantization error...
Barbara Hammer, Alexander Hasenfuss, Thomas Villma...
101
Voted
ISCAS
2005
IEEE
154views Hardware» more  ISCAS 2005»
15 years 7 months ago
Back propagation learning of neural networks with chaotically-selected affordable neurons
— Cell assembly is one of explanations of information processing in the brain, in which an information is represented by a firing space pattern of a group of plural neurons. On ...
Yoko Uwate, Yoshifumi Nishio
134
Voted
APIN
1998
139views more  APIN 1998»
15 years 1 months ago
Evolutionary Learning of Modular Neural Networks with Genetic Programming
Evolutionary design of neural networks has shown a great potential as a powerful optimization tool. However, most evolutionary neural networks have not taken advantage of the fact ...
Sung-Bae Cho, Katsunori Shimohara
IJCNN
2008
IEEE
15 years 8 months ago
Biologically realizable reward-modulated hebbian training for spiking neural networks
— Spiking neural networks have been shown capable of simulating sigmoidal artificial neural networks providing promising evidence that they too are universal function approximat...
Silvia Ferrari, Bhavesh Mehta, Gianluca Di Muro, A...
ICIP
1999
IEEE
16 years 3 months ago
Video Sequence Learning and Recognition Via Dynamic Som
Information contained in the video sequences is crucial for an autonomous robot or a computer to learn and respond to its surrounding environment. In the past, robot vision is mai...
Qiong Liu, Yong Rui, Thomas S. Huang, Stephen E. L...