In this work, a bibliographic analysis on artificial neural networks (ANNs) using fractional
calculus (FC) theory has been developed to summarize the main features and applications …

Artificial neural network (ANN) is the backbone of machine learning, specifically deep
learning. The interpolating and learning ability of an ANN makes it an ideal tool for …

This paper discusses the quasi-uniform synchronization issue for fractional-orderneural
networks (FONNs) with leakage and discrete delays. The impacts of leakage delay, discrete …

This article discusses the global Mittag-Leffler projective synchronization (GM-LPS) on
fractional-order quaternion-valued neural networks (FOQVNNs) including mixed delays and …

This paper is concerned with the global nonfragile Mittag-Leffler synchronization and the
global synchronization in finite time for fractional-order discontinuous neural networks …

In this paper, without separating the complex-valued neural networks into two real-valued
systems, the quasi-projective synchronization of fractional-order complex-valued neural …

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

This paper is concerned with the quasi-uniform synchronization (Q-US) issues of discrete
fractional fuzzy neural networks (DFFNNs) with time delays. Firstly, we analyze the neural …

Competitive neural networks (CNNs) has not been well developed in nonlinear fractional
order dynamical system, which is developed first time in this paper. Then, by means of a …

This article mainly concerns the synchronization in finite-time to the time-varying delay
fractional order memristive competitive neural networks (TMFCNNs) with leakage delay. By …