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- 1.0382475 - ÚI 2016 RIV US eng J - Journal Article
Frolov, A. - Húsek, Dušan - Polyakov, P.Y.
Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain.
IEEE Transactions on Neural Networks and Learning Systems. Roč. 27, č. 3 (2016), s. 538-550. ISSN 2162-237X. E-ISSN 2162-2388
R&D Projects: GA MŠMT ED1.1.00/02.0070
Institutional support: RVO:67985807
Keywords : associative memory * bars problem (BP) * Boolean factor analysis (BFA) * data mining * dimension reduction * Hebbian learning rule * information gain * likelihood maximization (LM) * neural network application * recurrent neural network * statistics
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 6.108, year: 2016
Permanent Link: http://hdl.handle.net/11104/0212684 - 2.0364125 - ÚI 2012 CZ eng K - Conference Paper (Czech conference)
Polyakov, P.Y. - Húsek, Dušan - Frolov, A. A.
Expectation-Maximization Method for Boolean Factor Analysis.
WOFEX 2011. Ostrava: VŠB - Technical University, 2011 - (Krátký, P.; Dvorský, J.; Moravec, P.), s. 436-441. ISBN 978-80-248-2449-9.
[WOFEX 2011. Annual Workshop /9./. Ostrava (CZ), 08.09.2011-09.09.2011]
Institutional research plan: CEZ:AV0Z10300504
Keywords : binary factor analysis * Boolean factor analysis * BFA * informational redundancy * high-dimensional binary signals * expectation–maximization method * EM * bars problem benchmark * dendritic inhibition neural network
Subject RIV: IN - Informatics, Computer Science
Permanent Link: http://hdl.handle.net/11104/0199688File Download Size Commentary Version Access a0364125.pdf 1 500.3 KB Publisher’s postprint require