SFr. 69.00
€ 74.52
BTC 0.0013
LTC 1.349
ETH 0.0332


bestellen

Artikel-Nr. 16881390


Diesen Artikel in meine
Wunschliste
Diesen Artikel
weiterempfehlen
Diesen Preis
beobachten

Weitersagen:



Autor(en): 
  • Adrian J. Shepherd
  • Second-Order Methods for Neural Networks: Fast and Reliable Training Methods for Multi-Layer Perceptrons 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  April 1997  
    Genre:  EDV / Informatik 
    ISBN:  9783540761006 
    EAN-Code: 
    9783540761006 
    Verlag:  Springer London 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 9 mm 
    Gewicht:  254 gr 
    Seiten:  160 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    About This Book This book is about training methods - in particular, fast second-order training methods - for multi-layer perceptrons (MLPs). MLPs (also known as feed-forward neural networks) are the most widely-used class of neural network. Over the past decade MLPs have achieved increasing popularity among scientists, engineers and other professionals as tools for tackling a wide variety of information processing tasks. In common with all neural networks, MLPsare trained (rather than programmed) to carryout the chosen information processing function. Unfortunately, the (traditional' method for trainingMLPs- the well-knownbackpropagation method - is notoriously slow and unreliable when applied to many prac­ tical tasks. The development of fast and reliable training algorithms for MLPsis one of the most important areas ofresearch within the entire field of neural computing. The main purpose of this book is to bring to a wider audience a range of alternative methods for training MLPs, methods which have proved orders of magnitude faster than backpropagation when applied to many training tasks. The book also addresses the well-known (local minima' problem, and explains ways in which fast training methods can be com­ bined with strategies for avoiding (or escaping from) local minima. All the methods described in this book have a strong theoretical foundation, drawing on such diverse mathematical fields as classical optimisation theory, homotopic theory and stochastic approximation theory.

      



    Wird aktuell angeschaut...
     

    Zurück zur letzten Ansicht


    AGB | Datenschutzerklärung | Mein Konto | Impressum | Partnerprogramm
    Newsletter | 1Advd.ch RSS News-Feed Newsfeed | 1Advd.ch Facebook-Page Facebook | 1Advd.ch Twitter-Page Twitter
    Forbidden Planet AG © 1999-2024
    Alle Angaben ohne Gewähr
     
    SUCHEN

     
     Kategorien
    Im Sortiment stöbern
    Genres
    Hörbücher
    Aktionen
     Infos
    Mein Konto
    Warenkorb
    Meine Wunschliste
     Kundenservice
    Recherchedienst
    Fragen / AGB / Kontakt
    Partnerprogramm
    Impressum
    © by Forbidden Planet AG 1999-2024