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000753337 019__ $$a934607994
000753337 020__ $$a9783319285184$$q(electronic book)
000753337 020__ $$a3319285181$$q(electronic book)
000753337 020__ $$z9783319285177
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000753337 0247_ $$a10.1007/978-3-319-28518-4$$2doi
000753337 035__ $$aSP(OCoLC)ocn934720531
000753337 035__ $$aSP(OCoLC)934720531$$z(OCoLC)934607994
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000753337 08204 $$a006.32$$223
000753337 1112_ $$aWorkshop on Self-Organizing Maps$$n(11th :$$d2016 :$$cHouston, Tex.)
000753337 24510 $$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 /$$cErzsébet Merényi, Michael J. Mendenhall, Patrick O'Driscoll, editors.
000753337 2463_ $$aWSOM 2016
000753337 264_1 $$aCham :$$bSpringer,$$c2016.
000753337 300__ $$a1 online resource (xiii, 370 pages) :$$billustrations.
000753337 336__ $$atext$$btxt$$2rdacontent
000753337 337__ $$acomputer$$bc$$2rdamedia
000753337 338__ $$aonline resource$$bcr$$2rdacarrier
000753337 4901_ $$aAdvances in Intelligent Systems and Computing,$$x2194-5357 ;$$vvolume 428
000753337 500__ $$aIncludes author index.
000753337 5050_ $$aSelf-Organizing Map Learning, Visualization, and Quality Assessment -- Clustering and Time Series Analysis with Self-Organizing Maps and Neural Gas.-Applications in Control, Planning, and Dimensionality Reduction, and Hardware for Self-Organizing Maps -- Self-Organizing Maps in Neuroscience and Medical Applications -- Learning Vector Quantization Theories and Applications I -- Learning Vector Quantization Theories and Applications II.
000753337 506__ $$aAccess limited to authorized users.
000753337 520__ $$aThis book contains the articles from the international conference 11th Workshop on Self-Organizing Maps 2016 (WSOM 2016), held at Rice University in Houston, Texas, 6-8 January 2016. WSOM is a biennial international conference series starting with WSOM'97 in Helsinki, Finland, under the guidance and direction of Professor Tuevo Kohonen (Emeritus Professor, Academy of Finland). WSOM brings together the state-of-the-art theory and applications in Competitive Learning Neural Networks: SOMs, LVQs and related paradigms of unsupervised and supervised vector quantization. The current proceedings present the expert body of knowledge of 93 authors from 15 countries in 31 peer reviewed contributions. It includes papers and abstracts from the WSOM 2016 invited speakers representing leading researchers in the theory and real-world applications of Self-Organizing Maps and Learning Vector Quantization: Professor Marie Cottrell (Universite Paris 1 Pantheon Sorbonne, France), Professor Pablo Estevez (University of Chile and Millennium Instituteof Astrophysics, Chile), and Professor Risto Miikkulainen (University of Texas at Austin, USA). The book comprises a diverse set of theoretical works on Self-Organizing Maps, Neural Gas, Learning Vector Quantization and related topics, and an excellent variety of applications to data visualization, clustering, classification, language processing, robotic control, planning, and to the analysis of astronomical data, brain images, clinical data, time series, and agricultural data.
000753337 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 14, 2016).
000753337 650_0 $$aNeural networks (Computer science)$$vCongresses.
000753337 650_0 $$aSelf-organizing maps$$vCongresses.
000753337 650_0 $$aSelf-organizing systems$$vCongresses.
000753337 7001_ $$aMerényi, Erzsébet,$$eeditor.
000753337 7001_ $$aMendenhall, Michael J.$$eeditor.
000753337 7001_ $$aO'Driscoll, Patrick,$$eeditor.
000753337 77608 $$iPrint version:$$tAdvances in self-organizing maps and learning vector quantization.$$d[Place of publication not identified] : Springer, 2016$$z3319285173$$z9783319285177$$w(OCoLC)930996923
000753337 830_0 $$aAdvances in intelligent systems and computing ;$$vv. 428.
000753337 852__ $$bebk
000753337 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-28518-4$$zOnline Access$$91397441.1
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