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 …

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 study, we investigate the global exponential stability of Clifford-valued neural network
(NN) models with impulsive effects and time-varying delays. By taking impulsive effects into …

In this paper, we first propose quaternion-valued neural networks (QVNNs) with unbounded
time-varying delays. Some sufficient conditions on the global μ-stability in the form of both …

In this paper, a novel kind of neural networks named fractional-order quaternion-valued
bidirectional associative memory neural networks (FQVBAMNNs) is formulated. On one …

This paper addresses the problem of robust stability for quaternion-valued neural networks
(QVNNs) with leakage delay, discrete delay and parameter uncertainties. Based on …

This paper talks about the stability and synchronization problems of fractional-order
quaternion-valued neural networks (FQVNNs) with linear threshold neurons. On account of …

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 …