Adaptive WTA with an analog VLSI neuromorphic learning chip

IEEE Transactions on Neural Networks

Volumn 18, Issue 2, 2007, Pages 551-572

  Häfliger, Philipp ^a  

^a UNIVERSITY OF OSLO   (Norway)

Author keywords

Classification; Competitive Hebbian learning; Neuromorphic electronics; Winner take all (WTA)

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE PROCESSING; LEARNING SYSTEMS; MICROPROCESSOR CHIPS; NEURAL NETWORKS;

COMPETITIVE HEBBIAN LEARNING; NEUROMORPHIC LEARNING; WINNER-TAKE-ALL (WTA);

VLSI CIRCUITS;

BIOMIMETIC MATERIAL;

ANALOG COMPUTER; ANALOG DIGITAL CONVERTER; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; EQUIPMENT; EQUIPMENT DESIGN; GAME; INSTRUMENTATION; SEMICONDUCTOR; SIGNAL PROCESSING;

ANALOG-DIGITAL CONVERSION; ARTIFICIAL INTELLIGENCE; BIOMIMETIC MATERIALS; COMPUTERS, ANALOG; EQUIPMENT DESIGN; EQUIPMENT FAILURE ANALYSIS; GAME THEORY; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; SEMICONDUCTORS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 34047217409     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2006.884676     Document Type: Article

References (47)

1. C. A. Mead, "Neuromorphic electronic systems," Proc. IEEE, vol. 78, no. 10, pp. 1629-1636, Oct. 1990.
2. A. L. Hodgkin and A. F. Huxley, "Current carried by sodium and potassium ions through the membrane of the giant axon of loglio," J. Physiol., vol. 116, p. 449, 1952.
3. K. Fukushima, Y. Yamaguchi, M. Yasuda, and S. Nagata, "An electronic model of the retina," Proc. IEEE, vol. 58, no. 12, pp. 1950-1951, Dec. 1970.
4. C. A. Mead and M. Mahowald, "A silicon model of early visual processing," Neural Netw., vol. 1, pp. 91-97, 1988.
5. C. Mead, Analog VLSI and Neural Systems. Reading, MA: Addison-Wesley, 1989.
6. A. G. Andreou and K. A. Boahen, "A contrast sensitive silicon retina with reciprocal synapses," in Advances in Neural Information Processing Systems (NIPS). Cambridge, MA: MIT Press, 1991, vol. 4, pp. 764-772.
7. K. A. Boahen, "The retinomorphic approach: Pixel-parallel adaptive amplification, filtering, and quantization," in Neuromorphic Systems Engineering, T. S. Lande, Ed. Norwell, MA: Kluwer, 1998, ch. 11.
8. E. Culurciello, R. Etienne-Cummings, and K. Boahen, "A biomorphic digital image sensor," IEEE J. Solid-State Circuits, vol. 38, no. 2, pp. 281-294, Feb. 2003.
9. M. Azadmehr, J. Abrahamsen, and P. Häfliger, "A foveated AER imager chip," in Proc. IEEE Int. Symp. Circuits Syst., Kobe, Japan, May 2005, vol. 3, pp. 2751-2754.
10. J. Lazzaro and C. A. Mead, "Circuit models of sensory transduction in the cochlea," in Analog VLSI Implementations Neural Networks, C. A. Mead and M. Ismail, Eds. Norwell, MA: Kluwer, 1989, pp. 85-101.
11. R. Sarpeshkar, R. F. Lyon, and C. Mead, "A Low-Power Wide-Dynamic-Range Analog VLSI Cochlea," in Neuromorphic Systems Engineering, T. S. Lande, Ed. Norwell, MA: Kluwer, 1998, ch. 3, pp. 49-103.
12. A. van Schaik and S.-C. Liu, "AER EAR: A matched silicon cochlea pair with address event representation interface," in Proc. IEEE Int. Symp. Circuits Syst., Kobe, Japan, 2005, vol. 5, pp. 4213-4216.
13. D. O. Hebb, The Organization of Behavior. New York: Wiley, 1949.
14. T. V. P. Bliss and T. Lømø, "Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path," J. Physiol., vol. 232, no. 2, pp. 331-356, Jul. 1973.
15. H. Markram, J. Lübke, M. Frotscher, and B. Sakmann, "Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs," Science, vol. 275, pp. 213-215, 1997.
16. S. Song, K. D. Miller, and L. F. Abbott, "Competitive Hebbian learning through spike-timing dependent synaptic plasticity," Nature Neurosci., vol. 3, pp. 919-926, 2000.
17. W. Gerstner, R. Kempter, J. van Hemmen, and H. Wagner, "A neuronal learning rule for sub-millisecond temporal coding," Nature, vol. 383, pp. 76-78, 1996.
18. P. Häfliger, M. Mahowald, and L. Watts, "A spike based learning neuron in analog VLSI," in Advances in Neural Information Processing Systems (NIPS). Cambridge, MA: MIT Press, 1996, vol. 9, pp. 692-698.
19. S. Fusi, M. Annunziato, D. Badoni, A. Salamon, and D. J. Amit, "Spike-driven synaptic plasticity: Theory, simulation, VLSI implementation," Neural Comput., vol. 12, pp. 2227-2258, 2000.
20. A. Bofill, A. F. Murray, and D. Thompson, "Circuits for VLSI implementation of temporally asymmetric Hebbian learning," in Advances in Neural Information Processing Systems (NIPS). Cambridge: MIT Press, 2001, vol. 14.
21. A. Bofill and A. F. Murray, "Synchrony detection by analogue VLSI neurons with bimodal STDP synapses," in Advances in Neural Information Processing Systems (NIPS). Cambridge, MA: MIT Press, 2003, vol. 16.
22. G. Indiveri, "Neuromorphic bistable VLSI synapses with spike-timing-dependent plasticity," in Advances in Neural Information Processing Systems (NIPS). Cambridge, MA: MIT Press, 2003, vol. 16.
23. K. Cameron, V. Boonsobhak, A. Murray, and D. Renshaw, "Spike timing dependent plasticity (STDP) can ameliorate process variations in neuromorphic VLSI," IEEE Trans. Neural Netw., vol. 16, no. 6, pp. 1626-1637, Nov. 2005.
24. G. Indiveri, E. Chicca, and R. Douglas, "A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity," IEEE Tran. Neural Netw., vol. 17, no. 1, pp. 211-221, Jan. 2006.
25. Z. Yang, A. Murray, F. Wörgötter, K. Cameron, and V. Boonsobhak, "A neuromorphic depth-from-motion vision model with STDP adaptation," IEEE Tran. Neural Netw., vol. 17, no. 2, pp. 482-495, Mar. 2006.
26. M. Holler, S. Tam, H. Castro, and R. Benson, "An electrically trainable artificial neural network (ETANN) with 10240 'floating gate' synapses," in Proc. Int. Joint Conf. Neural Netw., Jun. 1989, no. II, pp. 191-196.
27. C. Diorio, S. Mahajan, P. Hasler, B. Minch, and C. Mead, "A high-resolution non-volatile analog memory cell," in Proc. IEEE Intl. Symp. Circuits Syst., 1995, vol. 3, pp. 2233-2236.
28. P. Häfliger and H. K. Riis, "A multi-level static memory cell," in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), Bangkok, Thailand, May 2003, vol. 1, pp. 22-25.
29. R. Serrano-Gotarredona, M. Oster, P. Lichtsteiner, A. Linares-Barranco, R. Paz-Vicente, F. Gómez-Rodríguez, H. K. Riis, T. Delbrück, S. C. Liu, S. Zahnd, A. M. Whatley, R. Douglas, P. Häfliger, G. Jimenez-Moreno, A. Civit, T. Serrano-Gotarredona, A. Acosta-Jiménez, and B. Linares-Barranco, Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 2006, vol. 18.
30. M. Mahowald, An Analog VLSI System for Stereoscopic Vision. Norwell, MA: Kluwer, 1994.
31. A. Mortara and E. A. Vittoz, "A communication architecture tailored for analog VLSI artificial neural networks: Intrinsic performance and limitations," IEEE Trans. Neural Netw., vol. 5, no. 3, pp. 459-466, May 1994.
32. P. Lichtensteiner, C. Posch, and T. Delbrück, "A 128 × 128 120 db 30 mw asynchronous vision sensor that responds to relative intensity change," in Proc. ISSCC Dig. Tech. Papers, 2006, pp. 508-509.
33. A. Serrano-Gotarredona, T. Serrano-Gotarredona, A. J. Acosta-Jiménez, and B. Linares-Barranco, "An arbitrary kernel convolution AER-transceiver chip for real-time image filtering," in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), Kos, Greece, 2006, pp. 3145-3148.
34. M. Oster and S. C. Liu, "A winner-take-all spiking network with spiking inputs," in Proc. IEEE Int. Conf. Electron., Circuits Syst., Tel Aviv, Israel, 2004, pp. 203-206.
35. S. C. Liu and M. Oster, "Feature competition in a spike-based winner-take-all VLSI network," in Proc. IEEE Int. Symp. Circuits Syst., Kos, Greece, 2006, pp. 3634-3637.
36. P. Häfliger, "Asynchronous event redirecting in bio-inspired communication," in Proc. 8th IEEE Int. Conf. Electron., Circuits, Syst., Malta, Sep. 2001, vol. 1, pp. 87-90.
37. R. P. Vicente, F. G. Rodriguez, M. A. R. Jodar, A. L. Barranco, G. J. Moreno, and A. A. C. Balcells, "Test infrastructure for address-event-representation communications," in Lecture Notes in Computer Science. Berlin, Germany: Springer-Verlag, 2005, vol. 3512, pp. 518-526.
38. H. K. Riis and P. Häfliger, "An asynchronous 4-to-4 AER mapper," in Lecture Notes in Computer Science. Berlin, Germany: Springer-Verlag, 2005, vol. 3512, pp. 494-501.
39. P. Häfliger, "A spike based learning rule and its implementation in analog hardware" Ph.D. dissertation, ETH Zürich, Switzerland, 2000 [Online]. Available: http://www.ifi.uio.no/hafliger
40. R. Kempter, W. Gerstner, and J. L. van Hemmen, "Spike-based compared to rate-based Hebbian learning," Neural Inf. Process. Syst., vol. 11, pp. 125-131, 1999.
41. R. Kempter, W. Gerstner, and J. L. van Hemmen, Hebbian learning and spiking neurons," Phys. Rev. E, vol. 59, no. 4, pp. 4498-4514, 1999.
42. E. M. Izhikevich and N. S. Desai, "Relating STDP to BCM," Neural Comput., vol. 15, pp. 1511-1523, 2003.
43. J. Abrahamsen, P. Häfliger, and T. S. Lande, "A time domain winner-take-all network of integrate-and-fire neurons," in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), Vancouver, BC, Canada, May 2004, vol. V, pp. 361-364.
44. C. E. Shannon, "A mathematical theory of communication," in Claude Elwood Shannon Collected Papers, N. J. A. Solane and A. D. Wyner, Eds. Piscataway, NJ: IEEE Press, 1993.
45. A. Guazzelli, M. Bota, and M. A. Arbib, "Competitive Hebbian learning and the hippocampal place cell system: Modeling the interaction of visual and path integration cues," Hippocampus, vol. 11, pp. 216-239, 2001.
46. R. Yuste and W. Denk, "Dendritic spines as basic functional units of neuronal integration," Nature, vol. 375, pp. 682-684, 1995.
47. G. Stuart, N. Spruston, B. Sakmann, and M. Häusser, "Action potential initiation and backpropagation in neurons of the central nervous system," Trends Neurosci. (TINS), vol. 3, pp. 125-131, 1997.