Thesis - Department of Electronic & Computer Engineering

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8. ReferencesReferences1. John P. F. Sum, Chi-Sing Leung, Peter K. S. Tam, “Analysis for a Class ofWinner-Take-All model”, IEEE Trans. Neural Networks, Vol. 10, No. 1, Jan,1999.2. Kwabena Boahen, “Retinomorphic Vision Systems”, Proceedings of MicroNeuro’96.3. Charles M. Higgins and Christof Koch, “Multi-chip Neuromophic Motion Processing”,Proceedings 20th Anniversary Conference on Advanced Research inVLSI. IEEE Comput. Soc 1999 pp.309-23. Los Alamitos, CA, USA.4. Peter Adorjan, Lars Schwabe, “Recurrent cortical competition: Strengthen orweaken?”, Advances in Neural Information Processing Systems 12, MIT Press,Cambridge, MA, 2000.5. Zhaoping Li, “A Neural Model of Contour Integration in the Primary VisualCortex”, Neural Computation 10, 903-940 (1998).6. R.L.T Hahnloser, “On the piecewise analysis of networks of linear thresholdneurons”, Neural Networks 11 (1998) 691-697.7. Tetsuya Asai, Masashiro Ohtani, and Hiroo Yonezu, “Analog Integrated Circuitsfor the Lotka_Volterra Competitive Neural Networks”, IEEE Trans. NeuralNetworks, Vol. 10, No. 5, Sep, 1999.8. J. Lazzaro, S. Ryckebusch, M.A. Mahowald, and C. A. Mead, “Winner-take-allNetworks of O(N) Complexity, Advances in Neural Information ProcessingSystems I, 1988.9. T. G. Morris and S. P. Deweerth, “Analog VLSI Excitatory Feedback Circuitsfor Attention Shifts and Tracking”, Analog Integrated Circuits and Signal Processing,13, 79-91 (1997).78
10. “WTA networks with lateral excitation”, Analog Integrated Circuits & SignalProcessing, Vol. 13, No. 1-2, May-June, 1997, PP. 185-93.11. “CMOS Current Mode WTA Circuit with distributed…”, Electronics Letters,Vol. 31, No. 13, 22, June, 1995, pp. 1051-3.12. Alessandro Mortara, Eric A. Vittoz and Philippe Venier, “A communicationScheme for Analog VLSI Perceptive Systems”, IEEE Journal of Solid-StateCircuits, V.30, No.6, June, 1995.13. Maass and Bishop, Pulsed Neural Networks, 1999, Chapter 6 & 7, MIT Press.14. Kwabena A. Boahen, “Point-to-Point Connectivity Between NeuromorphicChips using Address-Events”, IEEE Trans. On Circuits & Systems, 1999.15. John Lazzaro and John Wawrzynek, “A Multi-Sender Asynchronous Extensionto the AER Protocol”, Proceedings. Sixteenth Conference on advancedResearch in VLSI. IEEE Comput. Soc. Press 1995, pp. 158-69, Los alamitos,CA, USA.16. Jan-tore Marienborg, Tor Sverre Lande, “Neuromorphic analog Communication”,ICNN96, The 1996 IEEE International Conference on Neural Networks.IEEE. Part Vol.2, 1996, pp. 920-5, Vol. 2, New York, NY, USA.17. A. Mortara and E. A. Vittoz, “A communication architecture tailored for analogVLSI neural networks: Intrinsic performance and limitation”, IEEE Trans.Neural Networks, Vo.5, No.3, pp. 459-66, May, 1994.18. P. Venier, A. Mortara, X. Arreguit, and E. Vittoz. “An Integrated Cortical Layerfor Orientation Enhancement”, IEEE Journal of Solid State Circuits, 32(2):177-186, Feb, 1997.19. Robert W. Adams, “Spectral Noise-Shaping in Integrate-and Fire Neural Networks”,1997 IEEE International Conference on Neural Networks. Proceedings.IEEE. Part Vol.2, 1997 pp. 953-8, Vol.2, New York, NY, USA.20. Alessandro Mortara, “A Pulsed Communication/Computation Framework forAnalog VLSI Perceptive Systems”, Analog Integrated Circuits & Signal Processing,Vol. 13, No. , May/June, 1997.79
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the system level. Our results show
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activities. The basin of attraction
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It is interesting to note that whic
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Although there is no saturation in
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• Response time of the system;As
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e verified by computer simulation (
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inhibition. Due to the fact that ea
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tion. Thus the power consumption is
Page 21 and 22:
Let∆be the minimum time necessary
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The sender initiates the sequence b
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Here in Table 1 is the comparison o
Page 27 and 28: source cell will be broadcast on th
Page 29 and 30: At this point, it seems appropriate
Page 31 and 32: detected, all the potential spikes
Page 33 and 34: InitializationFor each timestep ε
Page 35 and 36: global inhibition BusActivity to fr
Page 37 and 38: Spikes from the winnerATpTTT n T n+
Page 39 and 40: the network will either work at WTA
Page 41 and 42: The computer simulation results for
Page 43 and 44: 5.5 Steady State AnalysisAs demonst
Page 45 and 46: all the losers. To ensure that all
Page 47 and 48: 10090θ=θ mThe necessary condition
Page 49 and 50: 100Necessary conditions to exhibit
Page 51 and 52: The response time is estimated in t
Page 53 and 54: 5.6.2 Further study on the non-arbi
Page 55 and 56: 100Response time V.S. equivalent ga
Page 57 and 58: cell will never collide with each o
Page 59 and 60: ps ( i) = ( 1 - ϕ i)δ( s)for s =
Page 61 and 62: These results show that the collisi
Page 63 and 64: 5.7.4 SummaryCompared with the Pois
Page 65 and 66: 6. ConclusionsIn this thesis, a cla
Page 67 and 68: In this thesis, we consider only a
Page 69 and 70: v i() t≤I i----------- ( 1 - e1 -
Page 71 and 72: If a+ b - 1≥0, then τ---- d [ v
Page 73 and 74: If a+ b - 1 > 0, since v i() t > 0
Page 75 and 76: whereV ˙ i () t=max( v i ()0 t , )
Page 77: θ t s Nf f wp ct(%) p cl(%) p cw(%
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Thesis - Department of Electronic & Computer Engineering

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