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ICANN
2010
Springer
15 years 5 months ago
Unsupervised Learning of Relations
Learning processes allow the central nervous system to learn relationships between stimuli. Even stimuli from different modalities can easily be associated, and these associations ...
Matthew Cook, Florian Jug, Christoph Krautz, Angel...
GPEM
2006
82views more  GPEM 2006»
15 years 4 months ago
Shortcomings with using edge encodings to represent graph structures
There are various representations for encoding graph structures, such as artificial neural networks (ANNs) and circuits, each with its own strengths and weaknesses. Here we analyz...
Gregory Hornby
JCIT
2008
138views more  JCIT 2008»
15 years 4 months ago
Real Time Automated Fabric Defect Detection System using Microcontroller
In a Least Developed Country (LDC) like Bangladesh where the textile is the main core of our economy; still there is a major drawback in this sector which is the defect detection ...
Tamnun E. Mursalin, Fajrana Zebin Eishita, Ahmed R...
125
Voted
ALIFE
2004
15 years 4 months ago
Adaptability and Diversity in Simulated Turn-taking Behavior
Turn-taking behavior is simulated in a coupled-agents system. Each agent is modeled as a mobile robot with two wheels. A recurrent neural network is used to produce the motor outpu...
Hiroyuki Iizuka, Takashi Ikegami
BC
2002
90views more  BC 2002»
15 years 4 months ago
What can the hippocampal representation of environmental geometry tell us about Hebbian learning?
The importance of the hippocampus in spatial representation is well established. It is suggested that the rodent hippocampal network should provide an optimal substrate for the stu...
Colin Lever, Neil Burgess, Francesca Cacucci, Tom ...