30 March 2010 Probabilistic behavior and information measures of sequential nanoICs
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Due to many random factors from thermal fluctuation to wave interference, physical perfection in nanoICs is hard to achieve. Defects and faults arise from instability and noise-proneness on nanometer scales. This leads to unreliable and undesirable results of computation. In order to ensure more computation, techniques are necessary to cope with such errors. This can be achieved in nanotechnology using probabilistic models. In these models, it is assumed that the input and output signals are performed with probability because of noise signals, and the implemented logic function is performed within some probability because of the nature of nanoICs. In this paper, methods for computing the output probability of sequential logic nanocircuits are presented to extract information from sequential nanoICs in nanospace of a noisy environment, it is found that the most appropriate measure of information is the measure of entropy. The results of the study of probabilistic behavior and information measure of sequential nanoICs are reported with illustrative examples.
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Samuel C. Lee, Samuel C. Lee, } "Probabilistic behavior and information measures of sequential nanoICs", Proc. SPIE 7646, Nanosensors, Biosensors, and Info-Tech Sensors and Systems 2010, 76460Q (30 March 2010); doi: 10.1117/12.847438; https://doi.org/10.1117/12.847438


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