Recently, enormous datasets have made power dissipation and area usage lie at the heart
of designs for artificial neural networks (ANNs). Considering the significant role of activation …

The paper presents in detail a relatively simple implementation method of the hyperbolic
tangent function, particularly targeted for FPGAs. The research goal of the proposed method …

We propose and demonstrate a bidirectional Vanilla recurrent neural network (Vanilla-RNN)
based equalization scheme for O-band coarse wavelength division multiplexed (CWDM) …

This paper presents the high accuracy hardware implementation of the hyperbolic tangent
and sigmoid activation functions for artificial neural networks. A kind of a direct …

In this manuscript, an optically passive fiber Bragg grating (FBG) interrogation system able to
perform high-frequency measurement is proposed. The idea is mainly based on the use of …

This paper proposes a configurable Sigmoid and Tanh activation function circuit design by
second-order approximation and deviation compensation. The proposed circuit is …

Deep Neural Networks (DNNs) have gained significant popularity in several classification
and regression applications. The massive computation and memory requirements of DNNs …

Efficient implementation of non-linear activation functions is essential to the implementation
of deep learning models on FPGAs. We introduce such an implementation based on the …

In electric vehicles (EVs) with multiple motors, torque vectoring (TV) control can effectively
enhance the cornering response and safety. Moreover, TV systems can also improve the …

Many scientific and engineering applications can be formulated as a time-varying quadratic
programming (TVQP) problem, and effectively solving it is an attractive issue. In order to …