Most memristor-based neural networks only consider habituation under repeated stimuli, but
the emotional habituation under repeated emotional stimuli is ignored. In this article, a …

Monitoring and controlling of weld joint penetration are essential issues in variable polarity
plasma arc welding (VPPAW). In this paper, we develop a flexible visual sensor system to …

New chips for machine learning applications appear, they are tuned for a specific topology,
being efficient by using highly parallel designs at the cost of high power or large complex …

Machine learning algorithms such as those for object classification in images, video content
analysis, and human action recognition are used to extract meaningful information from data …

Abstract The Genetic Algorithm-Extreme Learning Machine (GA-ELM) neural network
algorithm is proposed to model the relevant characteristics of GaN pseudomorphic high …

In medical and health sciences, the detection of cell injury plays an important role in
diagnosis, personal treatment and disease prevention. Despite recent advancements in …

Currently, there are some emerging online learning applications handling data streams in
real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been …

In this paper the logarithmic Number System (LNS) is adopted to implement Long-Short
Term Memory (LSTM), the basic component of a deep learning network type. Initially, piece …

In the present scenario of technological breakthroughs in the automotive industry, machine
learning is greatly contributing to the development of safer and more comfortable vehicles. In …

All existing physiological tremor filtering algorithms, developed for robotic microsurgery, use
nonlinear phase prefilters to isolate the tremor signal. Such filters cause phase distortion to …