Abstract
We use neuromorphic chips to perform arbitrary mathematical computations for the first time. Static and dynamic computations are realized with heterogeneous spiking silicon neurons by programming their weighted connections. Using 4K neurons with 16M feed-forward or recurrent synaptic connections, formed by 256K local arbors, we communicate a scalar stimulus, quadratically transform its value, and compute its time integral. Our approach provides a promising alternative for extremely power-constrained embedded controllers, such as fully implantable neuroprosthetic decoders.
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References
Sarpeshkar, R., Delbruck, T., Mead, C.A.: White noise in MOS transistors and resistors. IEEE Circuits and Devices Magazine 9(6), 23–29 (1993)
Eliasmith, C., Anderson, C.H.: Neural engineering: computation, representation, and dynamics in neurobiological systems. MIT Press, Cambridge (2003)
Boahen, K.: A Burst-Mode Word-Serial Address-Event Link-I: Transmitter Design. IEEE Transactions on Circuits and Systems I 51(7), 1269–1280 (2004)
Silver, R., Boahen, K., Grillner, S., Kopell, N., Olsen, K.L.: Neurotech for neuroscience: unifying concepts, organizing principles, and emerging tools. Journal of Neuroscience 27(44), 11807–11819 (2007)
Gao, P., Benjamin, B.V., Boahen, K.: Dynamical system guided mapping of quantitative neuronal models onto neuromorphic hardware. IEEE Transactions on Circuits and Systems (in press, 2012)
Benjamin, B.V., Arthur, J.V., Gao, P., Merolla, P., Boahen, K.: A Superposable Silicon Synapse with Programmable Reversal Potential. In: International Conference of the IEEE Engineering and Medicine in Biology Society (in press, 2012)
Arthur, J.V., Boahen, K.A.: Synchrony in Silicon: The Gamma Rhythm. IEEE Transactions on Neural Networks 18(6), 1815–1825 (2007)
Goldberg, D.H., Cauwenberghs, G., Andreou, A.G.: Probabilistic synaptic weighting in a reconfigurable network of VLSI integrate-and-fire neurons. Neural Netw. 14(6-7), 781–793 (2001)
Andreou, A.G., Boahen, K.: Translinear circuits in subthreshold MOS. J. Anal. Integr. Circuits Signal Process 9, 141–166 (1996)
Dethier, J., Nuyujukian, P., Eliasmith, C., Stewart, T., Elassaad, S.A., Shenoy, K.V., Boahen, K.: A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm. In: Advances in Neural Information Processing Systems, vol. 24 (2011)
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Choudhary, S. et al. (2012). Silicon Neurons That Compute. In: Villa, A.E.P., Duch, W., Érdi, P., Masulli, F., Palm, G. (eds) Artificial Neural Networks and Machine Learning – ICANN 2012. ICANN 2012. Lecture Notes in Computer Science, vol 7552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33269-2_16
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DOI: https://doi.org/10.1007/978-3-642-33269-2_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33268-5
Online ISBN: 978-3-642-33269-2
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