An edition of Principles of artificial neural networks (2007)

Principles of artificial neural networks

2nd ed.

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Cover of: Principles of artificial neural networks by Daniel Graupe
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Last edited by ImportBot
August 17, 2023 | History
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An edition of Principles of artificial neural networks (2007)

Principles of artificial neural networks

2nd ed.

by

  • 0 Ratings
  • 0 Want to read
  • 0 Currently reading
  • 0 Have read

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Publish Date
Publisher
World Scientific
Language
English
Pages
303

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Previews available in: English

Subjects
Neural networks (Computer science), Neural networks (computer science)

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Edition Availability
Cover of: Principles of artificial neural networks
Principles of artificial neural networks
2007, World Scientific
in English - 2nd ed.
  • Not in Library
Libraries near you: WorldCat

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Book Details

Edition Notes

Includes bibliographical references (p. 291-297) and indexes.

Published in
Singapore, Hackensack, N.J
Series
Advanced series on circuits and systems -- vol. 6, Advanced series on circuits and systems -- v. 6.

Classifications

Library of Congress
QA76.87 G77 2007, QA76.87 .G77 2007, QA, QA76.87G77 2007

The Physical Object

Pagination
xv, 303 p. :
Number of pages
303

ID Numbers

Open Library
OL18285313M
Internet Archive
principlesartifi00grau_316
ISBN 10
9812706240
ISBN 13
9789812706249
LCCN
2008270006
OCLC/WorldCat
141384911
Library Thing
4561421
Goodreads
2193942

Source records

Library of Congress MARC record
Library of Congress MARC record
Internet Archive item record
Internet Archive item record
Library of Congress MARC record
Internet Archive item record
marc_columbia MARC record
Promise Item
Better World Books record

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History

Download catalog record: RDF / JSON / OPDS | Wikipedia citation
August 17, 2023 Edited by ImportBot import existing book
January 14, 2023 Edited by ImportBot import existing book
December 29, 2022 Edited by MARC Bot import existing book
May 28, 2022 Edited by ImportBot import existing book
October 15, 2008 Created by ImportBot Imported from Library of Congress MARC record