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 …

In the present study, a novel fractional Meyer neuro-evolution-based intelligent computing
solver (FMNEICS) is presented for numerical treatment of doubly singular multi-fractional …

This article considers the stabilization of highly nonlinear stochastic coupled systems
(HNSCSs) with time delay via periodically intermittent control. This article is motivated by …

The fractional neuro-evolution-based intelligent computing has substantial potential to solve
fractional order systems represented with Lane–Emden equation arising in astrophysics …

Nonlinear subspace clustering based on a feed-forward neural network has been
demonstrated to provide better clustering accuracy than some advanced subspace …

Surface Electromyogram (sEMG) signals, like other electrophysiological measurements, get
corrupted by several artefacts; much critical helpful information regarding a person's clinical …

In recent decades, fractional order calculus has become an important mathematical tool for
effectively solving complex problems through better modeling with the introduction of …

This paper proposes an efficient global gravitational search (GGS) algorithm-assisted
Kalman filter (KF) design, called a GGS-KF technique, for accurate estimation of the Volterra …

This paper analytically and numerically investigates the dynamical characteristics of a
fractional Duffing–van der Pol oscillator with two periodic excitations and the distributed time …

This study proposes a variable step-size saturation affine projection algorithm (VSS-sat-
APA) robust to impulsive noise. The proposed algorithm is analytically derived from the …