Effectively tackling the upcoming “zettabytes” data explosion requires a huge quantum leap
in our computing power and energy efficiency. However, with the Moore's law dwindling …

From last decade, lung cancer become sign of fear among the people all over the world. As
a result, many countries generate funds and give invitation to many scholars to overcome on …

Stochastic logic implementations of complex arithmetic functions, such as trigonometric,
exponential, and sigmoid, are derived based on truncated versions of their Maclaurin series …

Stochastic computing (SC) is a promising technique for applications that require low area
overhead and fault tolerance, but can tolerate relatively high latency. In the SC paradigm …

The rapid computerized simulation of stochastic computing (SC) systems is a challenging
problem. A method for agile simulation of SC image processing is proposed in this work. The …

This paper introduces memristors realized by molecular and DNA reactions. Molecular
memristors process one input molecule, generate two output molecules, and are realized …

This article considers implementation of artificial neural networks (ANNs) using molecular
computing and DNA based on fractional coding. Prior work had addressed molecular two …

Objective: As an effective lesion heterogeneity depiction, texture information extracted from
computed tomography has become increasingly important in polyp classification. However …

Stochastic computing (SC) is a re-emerging approach adopted in vision and learning
machines. SC, as a hardware-efficient unconventional computation paradigm, utilizes digital …

This paper introduces an analog-to-stochastic converter using a magnetic tunnel junction
(MTJ) device for vision chips based on stochastic computation. Stochastic computation has …