Geometric Algebra (GA) has proven to be an advanced language for mathematics, physics,
computer science, and engineering. This review presents a comprehensive study of works …

Quaternion neural networks have recently received an increasing interest due to noticeable
improvements over real-valued neural networks on real world tasks such as image, speech …

Abstract Machine Learning has recently emerged as a new paradigm for processing all
types of information. In particular, Artificial Intelligence is attractive to corporations & …

Experimental solid mechanics is at a pivotal point where machine learning (ML) approaches
are rapidly proliferating into the discovery process due to significant advances in data …

Recurrent neural networks (RNNs) are powerful architectures to model sequential data, due
to their capability to learn short and long-term dependencies between the basic elements of …

In this paper, we investigate the global stability of quaternion-valued neural networks
(QVNNs) with time-varying delays. On one hand, in order to avoid the noncommutativity of …

This paper proposes a quaternion-valued one-layer recurrent neural network approach to
resolve constrained convex function optimization problems with quaternion variables …

In this paper, we employ a novel method for solving the problem of the global exponential
stability of quaternion-valued recurrent neural networks (QVNNs) with time-varying delays …

Recently, the connectionist temporal classification (CTC) model coupled with recurrent
(RNN) or convolutional neural networks (CNN), made it easier to train speech recognition …

In this article, a class of quaternion-valued master–slave neural networks (NNs) with time-
varying delay and parameter uncertainties was first established by conducting the extension …