Advances in Neural Networks - ISNN 2010 [electronic resource] : 7th International Symposium on Neural Networks, ISNN 2010, Shanghai, China, June 6-9, 2010, Proceedings, Part I / edited by Liqing Zhang, Bao-Liang Lu, James Kwok.

Contributor(s): Zhang, Liqing [editor.] | Lu, Bao-Liang [editor.] | Kwok, James [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Computer Science ; 6063Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Description: XXIX, 757p. 185 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642132780Subject(s): Computer science | Computer software | Database management | Artificial intelligence | Computer vision | Optical pattern recognition | Computer Science | Computation by Abstract Devices | Image Processing and Computer Vision | Pattern Recognition | Artificial Intelligence (incl. Robotics) | Algorithm Analysis and Problem Complexity | Database ManagementAdditional physical formats: Printed edition:: No titleDDC classification: 004.0151 LOC classification: QA75.5-76.95Online resources: Click here to access online
Contents:
Neurophysiological Foundation -- Theory and Models -- Learning and Inference -- Neurodynamics.
In: Springer eBooksSummary: 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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Neurophysiological Foundation -- Theory and Models -- Learning and Inference -- Neurodynamics.

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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