Improving the accuracy of a neural network (NN) usually requires using larger hardware that
consumes more energy. However, the error tolerance of NNs and their applications allow …

Due to considerable effectiveness of the imprecise computing paradigm in hardware
implementation of many applications, great attention has been recently paid by many …

After almost a decade of research, development of more efficient imprecise computational
blocks is still a major concern in imprecise computing domain. There are many instances of …

In spite of the rapidly increasing number of approximate designs in circuit logic stack for
Artificial Neural Networks (ANNs) learning. A principled and systematic approximate …

Abstract Design space exploration of Low Power Approximate Adders (LPAAs) has become
significant as it successfully trades acceptable amounts of accuracy for the power, area, and …

Researchers traditionally solve the computational problems through rigorous and
deterministic algorithms called as Hard Computing. These precise algorithms have widely …