Scientific reports
Nov 17, 2022
The pair-contact process with diffusion (PCPD), a generalized model of the ordinary pair-contact process (PCP) without diffusion, exhibits a continuous absorbing phase transition. Unlike the PCP, whose nature of phase transition is clearly classified...
Neural networks : the official journal of the International Neural Network Society
Nov 13, 2022
A class of doubly stochastic graph shift operators (GSO) is proposed, which is shown to exhibit: (i) lower and upper L-boundedness for locally stationary random graph signals, (ii) L-isometry for i.i.d. random graph signals with the asymptotic increa...
Nature communications
Nov 7, 2022
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in th...
Journal of chemical theory and computation
Nov 1, 2022
We present two machine learning methodologies that are capable of predicting diffusion Monte Carlo (DMC) energies with small data sets (≈60 DMC calculations in total). The first uses voxel deep neural networks (VDNNs) to predict DMC energy densities ...
Neural networks : the official journal of the International Neural Network Society
Oct 10, 2022
This paper mainly attempts to discuss lag H synchronization in multiple state or derivative coupled reaction-diffusion neural networks without and with parameter uncertainties. Firstly, we respectively propose two types of reaction-diffusion neural n...
Neural networks : the official journal of the International Neural Network Society
Oct 8, 2022
This paper investigates the pinning synchronization of stochastic neutral memristive neural networks with reaction-diffusion terms. Firstly, two novel pinning controllers, which contain both current state and past state, are designed. Subsequently, i...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
This article investigates the stability and synchronization of nonautonomous reaction-diffusion neural networks with general time-varying delays. Compared with the existing works concerning reaction-diffusion neural networks, the main innovation of t...
IEEE transactions on nanobioscience
Sep 26, 2022
The unconventional nature of molecular communication necessitates contributions from a host of scientific fields making the simulator design for such systems to be quite challenging. The nervous system is one of the largest and most important nanonet...
IEEE transactions on neural networks and learning systems
Aug 31, 2022
For the considered reaction-diffusion inertial memristive neural networks (IMNNs), this article proposes a novel gain-scheduled generalized pinning control scheme, where three pinning control strategies are involved and 2 controller gains can be sche...
ISA transactions
Aug 20, 2022
The finite-time synchronization issue of reaction-diffusion memristive neural networks (RDMNNs) is studied in this paper. To better synchronize the parameter-varying drive and response systems, an innovative gain-scheduled integral sliding mode contr...