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pro vyhledávání: '"Bayesian Confidence Propagating Neural Networks"'
Autor:
Rajendran Bongole, Raghav
Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivit
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-324209
Autor:
Rajendran Bongole, Raghav
Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______260::0ef9aca82f343d7d08e3e4981b1ed2dd
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-324209
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-324209
Publikováno v:
Wavelet Analysis & Active Media Technology (In 3 Volumes) - Proceedings of the 6th International Progress; 2005, Issue 3, p1445-1450, 6p
The International Conference on Intelligent Computing (ICIC) was set up as an annual forum dedicated to emerging and challenging topics in the various aspects of advances in computational intelligence fields, such as artificial intelligence, machine