Deep learning based on neural networks has been widely used in image recognition,
speech recognition, natural language processing, automatic driving, and other fields and …

Recently, artificial intelligence applications have become part of almost all emerging
technologies around us. Neural networks, in particular, have shown significant advantages …

In this work, we demonstrate the offline FPGA realization of both recurrent and feedforward
neural network (NN)-based equalizers for nonlinearity compensation in coherent optical …

Lithium battery‐based electric vehicles (EVs) are gaining global popularity as an alternative
to combat the adverse environmental impacts caused by the utilization of fossil fuels. State of …

The use of the Hough transforms to identify shapes or images has been extensively studied
in the past using software for artificial intelligence applications. In this article, we present a …

In bioinformatics, alignment is an essential technique for finding similarities between
biological sequences. Usually, the alignment is performed with the Smith-Waterman (SW) …

In recent years, radar emitter signal recognition has enjoyed a wide range of applications in
electronic support measure systems and communication security. More and more deep …

The swift progress of electric vehicles (EVs) and hybrid electric vehicles (HEVs) has driven
advancements in battery management systems (BMS). However, optimizing the algorithms …

Recently, the combination of convolutional neural network (CNN) and long short-term
memory (LSTM) exhibits better performance than single network architecture. Most of these …

This paper presents the hardware realization of a real-time blood pressure (BP) prediction
model for wearable devices, utilizing long short-term memory (LSTM) deep neural networks …