Advances in Self-Organizing Maps and Learning Vector Quantization (Record no. 52599)

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fixed length control field 03887nam a22005055i 4500
001 - CONTROL NUMBER
control field 978-3-319-28518-4
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200420221251.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160107s2016 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319285184
-- 978-3-319-28518-4
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
245 10 - TITLE STATEMENT
Title Advances in Self-Organizing Maps and Learning Vector Quantization
Sub Title Proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2016.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIII, 370 p. 89 illus., 65 illus. in color.
490 1# - SERIES STATEMENT
Series statement Advances in Intelligent Systems and Computing,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Self-Organizing Map Learning, Visualization, and Quality Assessment -- Clustering and Time Series Analysis with Self-Organizing Maps and Neural Gas.-Applications in Control, Planning, and Dimensionality Reduction, and Hardware for Self-Organizing Maps -- Self-Organizing Maps in Neuroscience and Medical Applications -- Learning Vector Quantization Theories and Applications I -- Learning Vector Quantization Theories and Applications II.
520 ## - SUMMARY, ETC.
Summary, etc This book contains the articles from the international conference 11th Workshop on Self-Organizing Maps 2016 (WSOM 2016), held at Rice University in Houston, Texas, 6-8 January 2016. WSOM is a biennial international conference series starting with WSOM'97 in Helsinki, Finland, under the guidance and direction of Professor Tuevo Kohonen (Emeritus Professor, Academy of Finland). WSOM brings together the state-of-the-art theory and applications in Competitive Learning Neural Networks: SOMs, LVQs and related paradigms of unsupervised and supervised vector quantization. The current proceedings present the expert body of knowledge of 93 authors from 15 countries in 31 peer reviewed contributions. It includes papers and abstracts from the WSOM 2016 invited speakers representing leading researchers in the theory and real-world applications of Self-Organizing Maps and Learning Vector Quantization: Professor Marie Cottrell (Universite Paris 1 Pantheon Sorbonne, France), Professor Pablo Estevez (University of Chile and Millennium Instituteof Astrophysics, Chile), and Professor Risto Miikkulainen (University of Texas at Austin, USA). The book comprises a diverse set of theoretical works on Self-Organizing Maps, Neural Gas, Learning Vector Quantization and related topics, and an excellent variety of applications to data visualization, clustering, classification, language processing, robotic control, planning, and to the analysis of astronomical data, brain images, clinical data, time series, and agricultural data.
700 1# - AUTHOR 2
Author 2 Mer�enyi, Erzs�ebet.
700 1# - AUTHOR 2
Author 2 Mendenhall, Michael J.
700 1# - AUTHOR 2
Author 2 O'Driscoll, Patrick.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-28518-4
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
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-- Springer International Publishing :
-- Imprint: Springer,
-- 2016.
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
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-- Computational intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2194-5357 ;
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-- ZDB-2-ENG

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