As the metaverse gains attraction, the importance of metaverse security research becomes
increasingly evident. While there has been research on authenticating users in the …

In the development of the neural network (NN), the activation function has become more and
more important. The selection of the activation function indirectly affects the convergence …

Exponential functions are essential in many areas of science and engineering. Fast and
efficient computing of such functions in multiple floating-point formats is a complex task for …

Spintronic devices have been considered a promising candidate for the hardware
implementation of neural networks (NNs) due to their potential to address the contemporary …

Piecewise polynomial approximation (PPA) on nonlinear functions plays an important role in
high-precision computing. In this article, we proposed QPA, an integration of error-flattened …

Computing-in-memory (CIM) macros aiming at accelerating deep learning operations at low
power need activation function (AF) units on the same die to reduce their host-dependency …

We increase the power of the Artificial Neural Networks with the help of the Activation
Function (AF). The tansig and logsig are widely used AF. But there is still requires some …

Oryctes rhinoceros poses a significant threat to coconut plants in several coconut-producing
nations, including Rote Ndao District. Recognizing the distribution and severity of crop …

This dissertation presents symbolic loop compilation, the first full-fledged approach to
symbolically map loop nests onto tightly coupled processor arrays (TCPAs), a class of loop …

Comparison of most used activation functions in deep neural networks and their circuit
realizations in analog and digital neural Page 1 Comparison of most used activation …