Search results

  1. 1.
    0436431 - ÚTIA 2015 RIV US eng M - Monography Chapter
    Kučera, Vladimír
    Riccati Equations and their Solution.
    The Control Handbook, Second Edition: Control System Advanced Methods. Control System Advanced Methods. Boca Raton: CRC Press, 2011 - (Lewine, W.), s. 14.1-14.21. Electrical Engineering Handbook. ISBN 978-1-4200-7366-9
    R&D Projects: GA MŠk(CZ) 1M0567
    Institutional research plan: CEZ:AV0Z10750506
    Institutional support: RVO:67985556
    Keywords : Riccati equation * optimal control * solution
    Subject RIV: BC - Control Systems Theory
    http://library.utia.cas.cz/separaty/2011/TR/kucera-0436431.pdf
    Permanent Link: http://hdl.handle.net/11104/0240183
     
     
  2. 2.
    0433966 - ÚTIA 2015 RIV US eng M - Monography Chapter
    Kučera, Vladimír
    Algebraic Design Methods.
    The Control Handbook, Second Edition: Control System Advanced Methods. Control System Advanced Methods. Boca Raton: CRC Press, 2011 - (Lewine, W.), s. 21.1-21.21. Electrical Engineering Handbook. ISBN 978-1-4200-7366-9
    R&D Projects: GA MŠk(CZ) 1M0567
    Institutional research plan: CEZ:AV0Z10750506
    Institutional support: RVO:67985556
    Keywords : Control Systems * Advanced Methods * Methods Systems
    Subject RIV: BC - Control Systems Theory
    http://library.utia.cas.cz/separaty/2011/TR/kucera-0433966.pdf
    Permanent Link: http://hdl.handle.net/11104/0238120
     
     
  3. 3.
    0358973 - ÚI 2012 RIV HR eng M - Monography Chapter
    Jiřina, Marcel - Jiřina jr., M.
    Classifiers Based on Inverted Distances. Chapter 19.
    New Fundamental technologies in Data Mining. Rijeka: InTech, 2011 - (Funatsu, K.; Hasegawa, K.), s. 369-386. ISBN 978-953-307-547-1
    R&D Projects: GA MŠk(CZ) 1M0567
    Institutional research plan: CEZ:AV0Z10300504
    Keywords : classification * neighbor distances * correlation dimension * Zipfian distribution
    Subject RIV: BB - Applied Statistics, Operational Research
    http://www.intechopen.com/books/new-fundamental-technologies-in-data-mining/classifiers-based-on-inverted-distances
    Permanent Link: http://hdl.handle.net/11104/0196862
    FileDownloadSizeCommentaryVersionAccess
    0358973.pdf0878.8 KBAuthor´s preprintrequire
     
     
  4. 4.
    0342905 - ÚI 2011 RIV DE eng M - Monography Chapter
    Jiřina, Marcel - Jiřina jr., M.
    Genetic Selection Algorithm and Cloning for Data Mining with GMDH Method.
    Foundations of Computational Intelligence. Vol. 5. Berlin: Springer, 2009 - (Abraham, A.; Hassanien, A.; Snášel, V.), s. 359-376. Studies in Computational Intelligence, 205. ISBN 978-3-642-01535-9
    R&D Projects: GA MŠk(CZ) 1M0567
    Institutional research plan: CEZ:AV0Z10300504
    Keywords : GMDH method * genetic selection * cloning * classifier
    Subject RIV: IN - Informatics, Computer Science
    Permanent Link: http://hdl.handle.net/11104/0185513
     
     
  5. 5.
    0342904 - ÚI 2011 RIV DE eng M - Monography Chapter
    Jiřina, Marcel - Jiřina jr., M.
    Classification by the Use of Decomposition of Correlation Integral.
    Foundations of Computational Intelligence. Vol. 5. Berlin: Springer, 2009 - (Abraham, A.; Hassanien, A.; Snášel, V.), s. 39-55. Studies in Computational Intelligence, 205. ISBN 978-3-642-01535-9
    R&D Projects: GA MŠk(CZ) 1M0567
    Institutional research plan: CEZ:AV0Z10300504
    Keywords : classification * multifractal * correlation dimension * distribution mapping exponent
    Subject RIV: IN - Informatics, Computer Science
    Permanent Link: http://hdl.handle.net/11104/0185512
     
     
  6. 6.
    0328492 - ÚI 2010 RIV DE eng M - Monography Chapter
    Kůrková, Věra
    Estimates of Model Complexity in Neural-Network Learning.
    [Odhady modelové složitosti při učení neuronových sítí.]
    Innovations in Neural Information Paradigms and Applications. Berlin: Springer, 2009 - (Bianchini, M.; Maggini, M.; Scarselli, F.; Jain, L.), s. 97-111. Studies in Computational Intelligence, 247. ISBN 978-3-642-04002-3
    R&D Projects: GA MŠk(CZ) 1M0567
    Institutional research plan: CEZ:AV0Z10300504
    Keywords : model complexity * neural networks * learning from data
    Subject RIV: IN - Informatics, Computer Science
    Permanent Link: http://hdl.handle.net/11104/0174795
     
     


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