ISBN: 9780387906409 - learning algorithms theory and applications: theory and applications (3 Ergebnisse)

ISBN: 
Mit der Detailsuche verfeinern

Optimieren Sie Ihre Suche

  • Bücher (3)

bis

Benutzerdefinierte Preisspanne (EUR)

bis

  • Sprache: Englisch

    Verlag: Springer, 1981

    0387906401 / 9780387906409

    • Softcover

    Anbieter: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, Vereinigtes KönigreichHay-on-Wye Booksellers

    Verkäufer/-in mit 4 Sternen
    Verkäufer/-in kontaktieren

    Zustand: Gebraucht - Gut

    EUR 47,50

    EUR 29,96 Versand 
    Versand von Vereinigtes Königreich nach USA

    Anzahl: 1 verfügbar

    Zustand: Very Good. Slight fading to the spine of cover and name of previous owner inscribed on title page, otherwise in very good condition.

  • Sprache: Englisch

    Verlag: Springer Verlag, 1981

    0387906401 / 9780387906409

    • Softcover

    Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books

    Verkäufer/-in mit 5 Sternen
    Verkäufer/-in kontaktieren

    Zustand: Neu

    EUR 81,20

    EUR 11,99 Versand 
    Versand von Vereinigtes Königreich nach USA

    Anzahl: 2 verfügbar

    Paperback. Zustand: Brand New. 1st edition. 300 pages. 9.50x6.25x0.75 inches. In Stock.

  • Sprache: Englisch

    Verlag: Springer, 1981

    0387906401 / 9780387906409

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

    Verkäufer/-in mit 5 Sternen
    Verkäufer/-in kontaktieren

    Zustand: Neu

    EUR 66,40

    EUR 35,00 Versand 
    Versand von Deutschland nach USA

    Anzahl: 1 verfügbar

    Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Learning constitutes one of the most important phase of the whole psychological processes and it is essential in many ways for the occurrence of necessary changes in the behavior of adjusting organisms. In a broad sense influence of prior behavior and its consequence upon subsequent behavior is usually accepted as a definition of learning. Till recently learning was regarded as the prerogative of living beings. But in the past few decades there have been attempts to construct learning machines or systems with considerable success. This book deals with a powerful class of learning algorithms that have been developed over the past two decades in the context of learning systems modelled by finite state probabilistic automaton. These algorithms are very simple iterative schemes. Mathematically these algorithms define two distinct classes of Markov processes with unit simplex (of suitable dimension) as its state space. The basic problem of learning is viewed as one of finding conditions on the algorithm such that the associated Markov process has prespecified asymptotic behavior. As a prerequisite a first course in analysis and stochastic processes would be an adequate preparation to pursue the development in various chapters.…