Computer Arithmetics for Nanoelectronics by Vlad P Shmerko; Svetlana N Yanushkevich; Sergey Edward

By Vlad P Shmerko; Svetlana N Yanushkevich; Sergey Edward Lyshevski

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By Vlad P Shmerko; Svetlana N Yanushkevich; Sergey Edward Lyshevski

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The cell body in an artificial neural net is modeled by a linear activation function. 7 The number of neurons in the human brain is estimated to be 100 billions; mice and rats have 100 millions neurons, while honeybees and ants have 1 million neurons. Artificial neural networks can be designed and modeled to implement massively parallel architectures. A neural network is a network of nodes and links. The nodes are elementary computing units that could typify to some extent neurons assuming a conventional action potential premise.

An arbitrary Boolean function can be computed on a linear systolic array. Stochastic (probabilistic) computing is a fundamental concept in both contemporary design and nanocomputing. Envisioned nanotechnologyand molecular-based devices are expected to exhibit deterministic and stochastic electrochemomechanical phenomena that should be utilized to implement logic and memory functions. Stochastic computing promises to achieve fault tolerance by employing statistical principles in which deterministic logic signals are replaced with random variables.

Introduction 25 [8] Carbone A and Seeman NC. Circuits and programmable self-assembling DNA structures. In Proceedings of National Academy of Sciences, 99(20):12577– 12582, 2002. [9] Chakradhar ST, Agrawal VD, and Bushnell ML. Neural Models and Algorithms for Digital Testing. Kluwer, Dordrecht, 1991. [10] Chen J, Lee T, Su J, Wang W, Reed MA, Rawlett AM, Kozaki M, Yao Y, Jagessar RC, Dirk SM, Price DW, Tour JM, Grubisha DS, and Bennett DW. , Handbook of Molecular Nanoelectronics, American Science Publishers, New York, 2003.

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