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|a 9783642132780
|9 978-3-642-13278-0
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|a 10.1007/978-3-642-13278-0
|2 doi
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|a QA75.5-76.95
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|a 004.0151
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|a Advances in Neural Networks -- ISNN 2010
|h [electronic resource] :
|b 7th International Symposium on Neural Networks, ISNN 2010, Shanghai, China, June 6-9, 2010, Proceedings, Part I /
|c edited by James Kwok, Bao-Liang Lu, Liqing Zhang, Bao-Liang Lu.
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|a 1st ed. 2010.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2010.
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|a XXIX, 757 p. 185 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Theoretical Computer Science and General Issues,
|x 2512-2029 ;
|v 6063
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|a Neurophysiological Foundation -- Theory and Models -- Learning and Inference -- Neurodynamics.
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|a This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has become a well-established series of popular and high-quality conferences on neural computation and its applications. ISNN aims at providing a platform for scientists, researchers, engineers, as well as students to gather together to present and discuss the latest progresses in neural networks, and applications in diverse areas. Nowadays, the field of neural networks has been fostered far beyond the traditional artificial neural networks. This year, ISNN 2010 received 591 submissions from more than 40 countries and regions. Based on rigorous reviews, 170 papers were selected for publication in the proceedings. The papers collected in the proceedings cover a broad spectrum of fields, ranging from neurophysiological experiments, neural modeling to extensions and applications of neural networks. We have organized the papers into two volumes based on their topics. The first volume, entitled "Advances in Neural Networks- ISNN 2010, Part 1," covers the following topics: neurophysiological foundation, theory and models, learning and inference, neurodynamics. The second volume en- tled "Advance in Neural Networks ISNN 2010, Part 2" covers the following five topics: SVM and kernel methods, vision and image, data mining and text analysis, BCI and brain imaging, and applications.
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|a Computer science.
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|a Computer programming.
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|a Data structures (Computer science).
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|a Information theory.
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|a Computer vision.
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|a Pattern recognition systems.
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|a Artificial intelligence.
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|a Theory of Computation.
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|a Programming Techniques.
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|a Data Structures and Information Theory.
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|a Computer Vision.
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|a Automated Pattern Recognition.
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|a Artificial Intelligence.
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|a Kwok, James.
|e editor.
|0 (orcid)0000-0002-4828-8248
|1 https://orcid.org/0000-0002-4828-8248
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a Lu, Bao-Liang.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a Zhang, Liqing.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
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|a Lu, Bao-Liang.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9783642132773
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776 |
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|i Printed edition:
|z 9783642132797
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|a Theoretical Computer Science and General Issues,
|x 2512-2029 ;
|v 6063
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856 |
4 |
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|u https://doi.uam.elogim.com/10.1007/978-3-642-13278-0
|z Texto Completo
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|a ZDB-2-SCS
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|a ZDB-2-SXCS
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|a ZDB-2-LNC
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|a Computer Science (SpringerNature-11645)
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|a Computer Science (R0) (SpringerNature-43710)
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