By Longwen Huang, Si Wu (auth.), Liqing Zhang, Bao-Liang Lu, James Kwok (eds.)
This publication and its sister quantity gather refereed papers offered on the seventh Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. development at the good fortune of the former six successive ISNN symposiums, ISNN has turn into a well-established sequence of renowned and fine quality meetings on neural computation and its purposes. ISNN goals at delivering a platform for scientists, researchers, engineers, in addition to scholars to assemble jointly to give and speak about the newest progresses in neural networks, and purposes in various components. these days, the sector of neural networks has been fostered some distance past the normal man made neural networks. This 12 months, ISNN 2010 acquired 591 submissions from greater than forty international locations and areas. in accordance with rigorous studies, a hundred and seventy papers have been chosen for e-book within the court cases. The papers accrued within the lawsuits conceal a huge spectrum of fields, starting from neurophysiological experiments, neural modeling to extensions and functions of neural networks. we've geared up the papers into volumes in keeping with their subject matters. the 1st quantity, entitled “Advances in Neural Networks- ISNN 2010, half 1,” covers the subsequent issues: neurophysiological origin, idea and versions, studying and inference, neurodynamics. the second one quantity en- tled “Advance in Neural Networks ISNN 2010, half 2” covers the next 5 issues: SVM and kernel equipment, imaginative and prescient and photograph, information mining and textual content research, BCI and mind imaging, and applications.
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Extra info for Advances in Neural Networks - ISNN 2010: 7th International Symposium on Neural Networks, ISNN 2010, Shanghai, China, June 6-9, 2010, Proceedings, Part I
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IEEE Trans. Neural Netw. 8, 341–348 (1997) 2. : A Note on Convergence under Dynamical Thresholds with Delays. IEEE Trans. Neural Netw. 9, 231–233 (1998) 3. : Dynamics of Some Neural Network Models with Delay. Phys. Rev. E 63, 051906 (2001) 4. : Hopf Bifurcation and Chaos in A Single Delayed Neuron Equation with Non-Monotonic Activation Function. Chaos, Solitons and Fractals 12, 1535–1547 (2001) 5. : Stability Switches, Hopf Bifurcation and Chaos of A Neuron Model with Delay-Dependent Parameters.
The amplitude of oscillations always increases as the range parameter increases; the robustness of period against change in the range parameter occurs. Keywords: Bifurcation, Oscillations, Delay-dependent parameters. 1 Introduction For single neuron dynamics, Gopalsamy and Leung  proposed the following model of diﬀerential equation: x(t) ˙ = −x(t) + a tanh[x(t)] − ab tanh[x(t − τ )]. (1) Here, x(t) denotes the neuron response, and a and b are the range of the continuous variable x(t) and measure of the inhibitory inﬂuence from the past history, respectively.