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001 978-3-319-28518-4
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005 20200420221251.0
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020 _a9783319285184
_9978-3-319-28518-4
024 7 _a10.1007/978-3-319-28518-4
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aAdvances in Self-Organizing Maps and Learning Vector Quantization
_h[electronic resource] :
_bProceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 /
_cedited by Erzs�ebet Mer�enyi, Michael J. Mendenhall, Patrick O'Driscoll.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXIII, 370 p. 89 illus., 65 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Intelligent Systems and Computing,
_x2194-5357 ;
_v428
505 0 _aSelf-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 _aThis 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.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aMer�enyi, Erzs�ebet.
_eeditor.
700 1 _aMendenhall, Michael J.
_eeditor.
700 1 _aO'Driscoll, Patrick.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319285177
830 0 _aAdvances in Intelligent Systems and Computing,
_x2194-5357 ;
_v428
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-28518-4
912 _aZDB-2-ENG
942 _cEBK
999 _c52599
_d52599