Representations of Boolean Functions by Perceptron Networks

0432428 - ÚI 2015 RIV CZ eng C - Konferenční příspěvek (zahraniční konf.)
Kůrková, Věra
Representations of Boolean Functions by Perceptron Networks.
ITAT 2014. Information Technologies - Applications and Theory. Part II. Prague: Institute of Computer Science AS CR, 2014 - (Kůrková, V.; Bajer, L.; Peška, L.; Vojtáš, R.; Holeňa, M.; Nehéz, M.), s. 68-70. ISBN 978-80-87136-19-5.
[ITAT 2014. European Conference on Information Technologies - Applications and Theory /14./. Demänovská dolina (SK), 25.09.2014-29.09.2014]
Grant CEP: GA MŠMT(CZ) LD13002
Institucionální podpora: RVO:67985807
Klíčová slova: perceptron networks * model complexity * Boolean functions
Kód oboru RIV: IN - Informatika

Limitations of capabilities of shallow perceptron networks are investigated. Lower bounds are derived for growth of numbers of units and sizes of output weights in networks representing Boolean functions of d variables. It is shown that for large d, almost any randomly chosen Boolean function cannot be tractably represented by shallow perceptron networks, i.e., each its representation requires a network with number of units or sizes of output weights depending on d exponentially
Trvalý link: http://hdl.handle.net/11104/0236782