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ICANN
2005
Springer

Associative Learning in Hierarchical Self Organizing Learning Arrays

10 years 5 months ago
Associative Learning in Hierarchical Self Organizing Learning Arrays
In this paper we introduce feedback based associative learning in self-organized learning arrays (SOLAR). SOLAR structures are hierarchically organized and have the ability to classify patterns in a network of sparsely connected neurons. These neurons may define their own functions and select their interconnections locally, thus satisfying some of the requirements for biologically plausible intelligent structures. Feed-forward processing is used to make necessary correlations and learn the input patterns. Associations between neuron inputs are used to generate feedback signals. These feedback signals, when propagated to the associated inputs, can establish the expected input values. This can be used for hetero and auto associative learning and pattern recognition.
Janusz A. Starzyk, Zhen Zhu, Yue Li
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ICANN
Authors Janusz A. Starzyk, Zhen Zhu, Yue Li
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