By Quansheng Ren, Qiufeng Long, Zhiqiang Zhang, Jianye Zhao (auth.), Chengan Guo, Zeng-Guang Hou, Zhigang Zeng (eds.)
ISBN-10: 3642390641
ISBN-13: 9783642390647
ISBN-10: 364239065X
ISBN-13: 9783642390654
The two-volume set LNCS 7951 and 7952 constitutes the refereed court cases of the tenth foreign Symposium on Neural Networks, ISNN 2013, held in Dalian, China, in July 2013. The 157 revised complete papers provided have been rigorously reviewed and chosen from a variety of submissions. The papers are prepared in following issues: computational neuroscience, cognitive technology, neural community types, studying algorithms, balance and convergence research, kernel equipment, huge margin equipment and SVM, optimization algorithms, varational tools, keep watch over, robotics, bioinformatics and biomedical engineering, brain-like platforms and brain-computer interfaces, information mining and data discovery and different purposes of neural networks.
Read Online or Download Advances in Neural Networks – ISNN 2013: 10th International Symposium on Neural Networks, Dalian, China, July 4-6, 2013, Proceedings, Part I PDF
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Additional resources for Advances in Neural Networks – ISNN 2013: 10th International Symposium on Neural Networks, Dalian, China, July 4-6, 2013, Proceedings, Part I
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Journal of Neuroscience 27(35), 9247–9251 (2007) 13. jsp 14. html 15. : Neuromantic–from semi-manual to semi-automatic reconstruction of neuron morphology. Frontiers in Neuroinformatics 6(4), 1–14 (2012) 16. : Computer generation and quantitative morphometric analysis of virtual neurons. Anatomy and Embryology 204(4), 283–301 (2001) 17. : Branching dendritic trees and motoneuron membrane resistivity. Experimental Neurology 1(5), 491–527 (1959) 18. : Progress and perspectives in computational neuroanatomy.
In: 6th International Conference on Computer Sciences and Convergence Information Technology (ICCIT), pp. 618–621 (2011) 10. : A simplified dual neural network for quadratic programming with its KWTA application. IEEE Transactions on Neural Networks 17(6), 1500–1510 (2006) 11. : A K-Winners-Take-All Neural Network Based on Linear Programming Formulation. In: International Joint Conference on Neural Networks, IJCNN 2007, pp. 37–40 (2007) 12. : Finding the K shortest Loopless Paths in a Network. Management Science 17(11), 712–716 (1971) 13.
This means that the reduction of LRSs is naturally achieved by STDP-based learning, which can improve information transfer rate and give an inspiration for resolving the power consumption issue and the so called sneak path problem. Investigations with many kinds of parameter configurations prove that the aforementioned results are by no means accidental events. Though the memristor was for the first time discovered just in 2008, some researchers have made a great progress on hybrid nano-devices/semiconductor circuits.
Advances in Neural Networks – ISNN 2013: 10th International Symposium on Neural Networks, Dalian, China, July 4-6, 2013, Proceedings, Part I by Quansheng Ren, Qiufeng Long, Zhiqiang Zhang, Jianye Zhao (auth.), Chengan Guo, Zeng-Guang Hou, Zhigang Zeng (eds.)
by John
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