Počet záznamů: 1  

Energy-Time Tradeoff in Recurrent Neural Nets

  1. 1.
    SYSNO ASEP0472477
    Druh ASEPC - Konferenční příspěvek (mezinárodní konf.)
    Zařazení RIVD - Článek ve sborníku
    NázevEnergy-Time Tradeoff in Recurrent Neural Nets
    Tvůrce(i) Šíma, Jiří (UIVT-O) RID, SAI, ORCID
    Zdroj.dok.Artificial Neural Networks. Methods and Applications in Bio-/Neuroinformatics. - Cham : Springer, 2015 / Koprinkova-Hristova P. ; Mladenov V. ; Kasabov N.K. - ISSN 2193-9349 - ISBN 978-3-319-09902-6
    Rozsah strans. 51-62
    Poč.str.12 s.
    Forma vydáníTištěná - P
    AkceICANN 2013. International Conference on Artificial Neural Networks /23./
    Datum konání10.09.2013-13.09.2013
    Místo konáníSofia
    ZeměBG - Bulharsko
    Typ akceWRD
    Jazyk dok.eng - angličtina
    Země vyd.CH - Švýcarsko
    Klíč. slovaenergy complexity ; recurrent neural network ; finite automaton ; energy-time tradeoff
    Vědní obor RIVIN - Informatika
    CEPGBP202/12/G061 GA ČR - Grantová agentura ČR
    Institucionální podporaUIVT-O - RVO:67985807
    UT WOS000380528700003
    EID SCOPUS85008397780
    DOI10.1007/978-3-319-09903-3_3
    AnotaceIn this chapter, we deal with the energy complexity of perceptron networks which has been inspired by the fact that the activity of neurons in the brain is quite sparse (with only about 1% of neurons firing). This complexity measure has recently been introduced for feedforward architectures (i.e., threshold circuits). We shortly survey the tradeoff results which relate the energy to other complexity measures such as the size and depth of threshold circuits. We generalize the energy complexity for recurrent architectures which counts the number of simultaneously active neurons at any time instant of a computation. We present our energy-time tradeoff result for the recurrent neural nets which are known to be computationally as powerful as the finite automata. In particular, we show the main ideas of simulating any deterministic finite automaton by a low-energy optimal-size neural network. In addition, we present a lower bound on the energy of such a simulation (within a certain range of time overhead) which implies that the energy demands in a fixedsize network increase exponentially with the frequency of presenting the input bits.
    PracovištěÚstav informatiky
    KontaktTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Rok sběru2017
Počet záznamů: 1  

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