By Haruo Hosoya (auth.), Kok Wai Wong, B. Sumudu U. Mendis, Abdesselam Bouzerdoum (eds.)
ISBN-10: 3642175368
ISBN-13: 9783642175367
ISBN-10: 3642175376
ISBN-13: 9783642175374
The quantity set LNCS 6443 and LNCS 6444 constitutes the complaints of the seventeenth overseas convention on Neural info Processing, ICONIP 2010, held in Sydney, Australia, in November 2010. The 146 common consultation papers awarded have been rigorously reviewed and chosen from 470 submissions. The papers of half I are equipped in topical sections on neurodynamics, computational neuroscience and cognitive technology, facts and textual content processing, adaptive algorithms, bio-inspired algorithms, and hierarchical equipment. the second one quantity is based in topical sections on mind computing device interface, kernel tools, computational enhance in bioinformatics, self-organizing maps and their purposes, laptop studying purposes to snapshot research, and applications.
Read or Download Neural Information Processing. Theory and Algorithms: 17th International Conference, ICONIP 2010, Sydney, Australia, November 22-25, 2010, Proceedings, Part I PDF
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Extra info for Neural Information Processing. Theory and Algorithms: 17th International Conference, ICONIP 2010, Sydney, Australia, November 22-25, 2010, Proceedings, Part I
Example text
Figures 3e and f show the curvature segments detected (in Step 2) for an input shape similar to the one in Figure 2 of Pasupathy & Connor (2002) [7]. The spots on the contour in Figure 3e indicate representative points of each curvature segment. The relative curvature and angular positions of each segment are indicated in Figure 3f, which shows a good correspondence between the representation of the shape by the model and V4 curvature neurons (presented in Fig. 2b of [7]). 4), the input shape was successfully reconstructed by our model from detected curvatures that were then represented in full feature space (Fig.
75 μM and [B] = 30 μM. The d(i) is the Ca2+ diffusion length through the membrane. 60 which is a fluorescent protein often used in C. elegans. 60 indicator reacts with intracellular Ca2+ and is luminiferous in a neuron. The fluorescence intensity Y (i) is calculated from the intracellular calcium concentration as follows. 7. 5 ICa (μA/cm2) V (mV) Iinput (pA/cm2) Quantitative Modeling of Neuronal Dynamics in C. elegans 200 (e) 100 0 -60 -40 -20 0 V (mV) 0 (f) -50 -100 -60 -40 -20 0 V (mV) Fig. 2. Neuronal responses of the single neuron to current injections.
The presynaptic spike output is transmitted to the connected neuron according to PSP with the weight connection. 0). Therefore, the postsynaptic action potential is excitatory if the weight parameter, wj,i is positive. If the condiPSP PSP tion hj (t − 1) < hi (t) is satisfied, the weight parameter is trained based on the temporal Hebbian learning rule as follows, ( w j,i ← tanh γ wgt ⋅ w j,i + ξ wgt ⋅ h jPSP (t − 1) ⋅ hiPSP (t) ) (6) where γwht is a discount rate and ξwgt is a learning rate. We apply the SNN to the human localization based on measured data of the sensor networks.
Neural Information Processing. Theory and Algorithms: 17th International Conference, ICONIP 2010, Sydney, Australia, November 22-25, 2010, Proceedings, Part I by Haruo Hosoya (auth.), Kok Wai Wong, B. Sumudu U. Mendis, Abdesselam Bouzerdoum (eds.)
by Richard
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