Abstract
Biological systems provide good architectural models for information processing hardware. Difficult problems in machine perception and complex motor control are solved in a natural way by energy efficient and robust neural systems. Hopfield in his seminal paper [1] on physical systems with emergent computational abilities envisioned a new breed of integrated circuits that could implement such systems and would be much less sensitive to element failure than present day computers. Analog VLSI is a technology suitable for the implementation of synthetic neural systems [2, 3] on silicon.
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References
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Andreou, A.G., Kontogiorgis, S.A. (1990). Fault Tolerance in Analog VLSI: Case Study of a Focal Plane Processor. In: Stapper, C.H., Jain, V.K., Saucier, G. (eds) Defect and Fault Tolerance in VLSI Systems. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9957-6_19
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DOI: https://doi.org/10.1007/978-1-4757-9957-6_19
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