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Record Nr. |
UNISA996465534003316 |
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Titolo |
Advances in Neural Networks - ISNN 2008 [[electronic resource] ] : 5th International Composium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part II / / edited by Fuchun Sun, Jianwei Zhang, Jinde Cao, Wen Yu |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008 |
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ISBN |
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Edizione |
[1st ed. 2008.] |
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Descrizione fisica |
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1 online resource (XXXI, 846 p.) |
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Collana |
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Theoretical Computer Science and General Issues, , 2512-2029 ; ; 5264 |
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Disciplina |
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Soggetti |
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Computer programming |
Data mining |
Computer simulation |
Computer science |
Artificial intelligence |
Computer vision |
Programming Techniques |
Data Mining and Knowledge Discovery |
Computer Modelling |
Theory of Computation |
Artificial Intelligence |
Computer Vision |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Machine Learning and Data Mining -- Intelligent Control and Robotics -- Pattern Recognition -- Audio, Image Processing and Computer Vision -- Fault Diagnosis -- Other Applications and Implementations -- Applications of Neural Networks in Electronic Engineering -- Cellular Neural Networks and Advanced Control with Neural Networks -- Nature Inspired Methods of High-dimensional Discrete Data Analysis -- Pattern Recognition and Information Processing Using Neural Networks. |
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Sommario/riassunto |
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The two volume set LNCS 5263/5264 constitutes the refereed |
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proceedings of the 5th International Symposium on Neural Networks, ISNN 2008, held in Beijing, China in September 2008. The 192 revised papers presented were carefully reviewed and selected from a total of 522 submissions. The papers are organized in topical sections on computational neuroscience; cognitive science; mathematical modeling of neural systems; stability and nonlinear analysis; feedforward and fuzzy neural networks; probabilistic methods; supervised learning; unsupervised learning; support vector machine and kernel methods; hybrid optimisation algorithms; machine learning and data mining; intelligent control and robotics; pattern recognition; audio image processinc and computer vision; fault diagnosis; applications and implementations; applications of neural networks in electronic engineering; cellular neural networks and advanced control with neural networks; nature inspired methods of high-dimensional discrete data analysis; pattern recognition and information processing using neural networks. |
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