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Vol. 5  No. 3 (2019) · Articles

PROBABILISTIC BLUNDERS MODELING FOR APPROXIMATE ADDERS

Professor.Jaganmohan Rao.S
Professor, Dept of ECE, Ramachandra College of Engineering, Eluru, A.P.India , IN

M.Rani Kamala
Professor, Dept of ECE, Ramachandra College of Engineering, Eluru, A.P.India , IN

📅 Published: March 2019

Keywords: Approximate computing, adders, probability of error, probability mass function (PMF), image smoothing, modeling, arithmetic, analysis.

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Abstract

Approximate adders are used in applications that are error tolerant to save on power and area. Basically, in error resilient applications, approximate adders are used to obtain high performance gain. In this paper we presented a analytical model for approximate adders (i.e.) Probability Mass Function (PMF). This PMF unit consists of sub adder units which are in uniform as well as non-uniform lengths. A closed form of expression is derived for the error probability to obtain high performance. By using arbitrary input distributions the analytical part is determined. By using the proposed error model, we can estimate the probability of error in circuits with multiple approximate adders. The proposed error model is most widely used in practical applications of image processing. Therefore the proposed designs achieve the best tradeoff between accuracy, delay and power.

How to Cite

Professor.Jaganmohan Rao.S, M.Rani Kamala, “PROBABILISTIC BLUNDERS MODELING FOR APPROXIMATE ADDERS,” International Journal of Technical Innovation in Modern Engineering & Science, vol. 5, no. 3, pp. 311-316, March 2019.

References

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