This paper addresses the robust speech recognition problem as a domain adaptation task.
Specifically, we introduce an unsupervised deep domain adaptation (DDA) approach to …

To solve online continuous time-varying convex quadratic-programming problems
constrained by a time-varying linear-equality, a novel varying-parameter convergent …

In recent years, grid-connected residential PV generation systems have been greatly
encouraged in China. In a residential power system containing PV, three types of power …

This article mainly explores the global h-stability for proportional delay high-order inertial
neural networks. Without adopting reduced order method, a new Lyapunov–Krasovskii …

Computing time-varying linear systems is widely encountered in engineering practice and
scientific computation. Dynamic neural networks, as a class of modeling approaches, have …

Time-variant problems are widespread in science and engineering, and discrete-time
recurrent neurodynamics (DTRN) method has been proved to be an effective way to deal …

This article proposes a novel fixed-time converging forward-backward-forward
neurodynamic network (FXFNN) to deal with mixed variational inequalities (MVIs). A …

This article focuses on the research of a general time-varying nonlinear optimization (TVNO)
problem solving especially in a noise-disturbance environment. For addressing this problem …

This paper focuses on the global Mittag–Leffler (M–L) synchronization for fractional-order
inertial neural networks (FOINNs) including the Caputo derivative and delay. By choosing an …

We focus on the fixed-time convergence and robustness of gradient-based dynamic
networks for solving convex optimization. Most of the existing gradient-based dynamic …