AIMC Topic: Diffusion

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Event-triggered impulsive cluster synchronization of coupled reaction-diffusion neural networks and its application to image encryption.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the cluster synchronization of coupled neural networks with reaction-diffusion terms. With the help of impulsive control strategies, some cluster synchronization criteria are proposed by an appropriate event-triggered mechanis...

Preassigned-time synchronization for complex-valued memristive neural networks with reaction-diffusion terms and Markov parameters.

Neural networks : the official journal of the International Neural Network Society
This study addresses the preassigned-time synchronization for complex-valued memristive neural networks with reaction-diffusion terms and Markov parameters. Employing a preassigned-time stable control strategy, two distinct controllers with varying p...

Inferring pointwise diffusion properties of single trajectories with deep learning.

Biophysical journal
To characterize the mechanisms governing the diffusion of particles in biological scenarios, it is essential to accurately determine their diffusive properties. To do so, we propose a machine-learning method to characterize diffusion processes with t...

Double graph correlation encryption based on hyperchaos.

PloS one
Preventing unauthorized access to sensitive data has always been one of the main concerns in the field of information security. Accordingly, various solutions have been proposed to meet this requirement, among which encryption can be considered as on...

Adv-BDPM: Adversarial attack based on Boundary Diffusion Probability Model.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks have become increasingly significant in our daily lives due to their remarkable performance. The issue of adversarial examples, which are responsible for the vulnerability problem of deep neural networks, has attracted the attent...

Design of New Inorganic Crystals with the Desired Composition Using Deep Learning.

Journal of chemical information and modeling
New solid-state materials have been discovered using various approaches from atom substitution in density functional theory (DFT) to generative models in machine learning. Recently, generative models have shown promising performance in finding new ma...

Multiobjective Molecular Optimization for Opioid Use Disorder Treatment Using Generative Network Complex.

Journal of medicinal chemistry
Opioid use disorder (OUD) has emerged as a significant global public health issue, necessitating the discovery of new medications. In this study, we propose a deep generative model that combines a stochastic differential equation (SDE)-based diffusio...

Robotic Surgery in Urology: History from PROBOT to HUGO.

Sensors (Basel, Switzerland)
The advent of robotic surgical systems had a significant impact on every surgical area, especially urology, gynecology, and general and cardiac surgery. The aim of this article is to delineate robotic surgery, particularly focusing on its historical ...

Adaptive pinning cluster synchronization of a stochastic reaction-diffusion complex network.

Neural networks : the official journal of the International Neural Network Society
This work aims to achieve cluster synchronization of a complex network by some pinning control strategies. Firstly, the network not only is affected by the reaction-diffusion and the directed coupling phenomena, but also is disturbed by the stochasti...

Adaptive event-triggered extended dissipative synchronization of delayed reaction-diffusion neural networks under deception attacks.

Neural networks : the official journal of the International Neural Network Society
Under spatially averaged measurements (SAMs) and deception attacks, this article mainly studies the problem of extended dissipativity output synchronization of delayed reaction-diffusion neural networks via an adaptive event-triggered sampled-data (A...