Emerging Intelligent Computing Technology and Applications: by Zhifeng Hao, Jinlong Huang, Ruichu Cai, Wen Wen (auth.),

By Zhifeng Hao, Jinlong Huang, Ruichu Cai, Wen Wen (auth.), De-Shuang Huang, Phalguni Gupta, Ling Wang, Michael Gromiha (eds.)

This e-book constitutes the refereed complaints of the ninth overseas convention on clever Computing, ICIC 2013, held in Nanning, China, in July 2013. The 192 revised complete papers awarded within the 3 volumes LNCS 7995, LNAI 7996, and CCIS 375 have been rigorously reviewed and chosen from 561 submissions. The papers during this quantity (CCIS 375) are geared up in topical sections on Neural Networks; platforms Biology and Computational Biology; Computational Genomics and Proteomics; wisdom Discovery and knowledge Mining; Evolutionary studying and Genetic Algorithms; desktop studying conception and techniques; Biomedical Informatics idea and techniques; Particle Swarm Optimization and area of interest know-how; Unsupervised and Reinforcement studying; clever Computing in Bioinformatics; clever Computing in Finance/Banking; clever Computing in Petri Nets/Transportation structures; clever Computing in sign Processing; clever Computing in development acceptance; clever Computing in picture Processing; clever Computing in Robotics; clever Computing in laptop imaginative and prescient; exact consultation on Biometrics process and defense for clever Computing; exact consultation on Bio-inspired Computing and functions; computing device Human interplay utilizing a number of visible Cues and clever Computing; targeted consultation on Protein and Gene Bioinformatics: research, Algorithms and Applications.

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Huang et al. ): ICIC 2013, CCIS 375, pp. 13–18, 2013. © Springer-Verlag Berlin Heidelberg 2013 14 C. Yang, X. Zhou, and T. Wang in this paper, we shall further study the following impulsive neural networks with time-varying delays:  x i(t ) = −hi ( xi (t )) + fi ( x1 (t ),, xn (t ), x1 (t − τ i1 (t )),, xn (t − τ in (t ))) + Ii ,  t > t0 , t ≠ tk , i ∈ N = {1, 2,, n},   + − Δxi (tk ) = xi (tk ) − xi (tk ) = J k ( xi (tk )), k ∈ Z = {1, 2, },  xi ( s) = ϕi (s), s ∈[t0 − τ , t0 ], where (2) hi (xi (t)) is an appropriately behaved function at time t and τij (t) is the tran- sition delay, which is time-varying and bounded with 0 ≤ τ ij (t ) ≤ τ .

Neuron. 55(2), 179–186 (2007) 7. : On and Off Pathways in the Vertebrate Retina and Visual System. MIT Press, Cambridge (2003) 8. : Spiking Neural Network Performs Discrete Cosine Transform for Visual Images. Emerging Intelligent Computing Technology and Applications: With Aspects of Artificial Intelligence 5755, 21–29 (2009) 9. : Ten Lectures On Wavelets. Society for Industrial and Applied Mathematics 61 (1992) 10. : An Introduction to Wavelets. Academic Press, New York (1992) 11. edu 12. : A theory for multiresolution signal decomposition: the wavelet representation 11, 674–693 (1989) 13.

Springer-Verlag Berlin Heidelberg 2013 13 13 6 6 23 23 6 6 33 33 6 6 43 43 3 3 53 53 3 3 63 63 3 3 (1) 20 C. Feng and Y. Lin By means of Chafee’s limit cycle criterion [10]: If system (1) has a unique unstable equilibrium point, all solutions of the system are bounded, then system (1) will generate a limit cycle, namely a periodic solution. Our restrictive conditions are weaker than the conditions in [6]. 2 Preliminaries Assume that (C1) For i = 1, 2, ,6, j = 1, 2,3, fij ( u ) are continuous bounded monotone increasing (or decreasing) activation functions.

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