Advances in neural network research and applications / edited by Zhigang Zeng, Jun Wang
- 作者： International Symposium on Neural Networks (7th : 2010 : Shanghai, China)
- 其他作者：
- 其他題名：
- Springer eBooks
- ISNN 2010
- 出版： Berlin, Heidelberg : Springer Berlin Heidelberg 2010
- 叢書名： Lecture notes in electrical engineering ,v.67
- 主題： Neural networks (Computer science)--Congresses. , Engineering. , Power Electronics, Electrical Machines and Networks. , Computational intelligence , Artificial Intelligence (incl. Robotics) , Control.
- ISBN： 9783642129902 (electronic bk.) 、 9783642129896 (paper)
- URL：
電子書
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讀者標籤：
- 系統號： 005172875 | 機讀編目格式
館藏資訊
This book is a part of the Proceedings of the Seventh International Symposium on Neural Networks (ISNN 2010), held on June 6-9, 2010 in Shanghai, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural networks and related fields, with a successful sequence of ISNN series in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), Beijing (2008), and Wuhan (2009). Following the tradition of ISNN series, ISNN 2010 provided a high-level international forum for scientists, engineers, and educators to present the state-of-the-art research in neural networks and related fields, and also discuss the major opportunities and challenges of future neural network research. Over the past decades, the neural network community has witnessed significant breakthroughs and developments from all aspects of neural network research, including theoretical foundations, architectures, and network organizations, modeling and simulation, empirical studies, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, has provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large scale, and networked brain-like intelligent systems. This long-term goals can only be achieved with the continuous efforts from the community to seriously investigate various issues on neural networks and related topics.