AIMC Topic: Diffusion

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Anomalous diffusion dynamics of learning in deep neural networks.

Neural networks : the official journal of the International Neural Network Society Feb 3, 2022
Learning in deep neural networks (DNNs) is implemented through minimizing a highly non-convex loss function, typically by a stochastic gradient descent (SGD) method. This learning process can effectively find generalizable solutions at flat minima. I...
Neural Networks, Computer Algorithms Diffusion
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Neural Network Method for Diffusion-Ordered NMR Spectroscopy.

Analytical chemistry Feb 2, 2022
Diffusion-ordered NMR spectroscopy (DOSY) presents an essential tool for the analysis of compound mixtures by revealing intrinsic diffusion behaviors of the mixed components. For the interpretation of the diffusion information, intrinsically designed...
Neural Networks, Computer Algorithms Diffusion Magnetic Resonance Spectroscopy
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Event-triggered H/passive synchronization for Markov jumping reaction-diffusion neural networks under deception attacks.

ISA transactions Dec 30, 2021
The issue of H/passive master-slave synchronization for Markov jumping neural networks with reaction-diffusion terms is investigated in this paper via an event-triggered control scheme under deception attacks. To lighten the burden of limited communi...
Neural Networks, Computer Communication Deception Diffusion
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Space-Dividing-Based Cluster Synchronization of Reaction-Diffusion Genetic Regulatory Networks via Intermittent Control.

IEEE transactions on nanobioscience Dec 30, 2021
In this paper, we focus on the cluster synchronization of reaction-diffusion genetic regulatory networks (RDGRNs) with time-varying delays, where the state of the system is not only time-dependent but also spatially-dependent due to the presence of t...
Neural Networks, Computer Gene Regulatory Networks Diffusion
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Quantized Sampled-Data Synchronization of Delayed Reaction-Diffusion Neural Networks Under Spatially Point Measurements.

IEEE transactions on cybernetics Dec 22, 2021
This article considers the synchronization problem of delayed reaction-diffusion neural networks via quantized sampled-data (SD) control under spatially point measurements (SPMs), where distributed and discrete delays are considered. The synchronizat...
Neural Networks, Computer Time Factors Diffusion
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Reconstructing Unsteady Flow Data From Representative Streamlines via Diffusion and Deep-Learning-Based Denoising.

IEEE computer graphics and applications Dec 10, 2021
We propose VFR-UFD, a new deep learning framework that performs vector field reconstruction (VFR) for unsteady flow data (UFD). Given integral flow lines (i.e., streamlines), we first generate low-quality UFD via diffusion. VFR-UFD then leverages a c...
Neural Networks, Computer Algorithms Deep Learning Diffusion Time
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Pinning bipartite synchronization for coupled reaction-diffusion neural networks with antagonistic interactions and switching topologies.

Neural networks : the official journal of the International Neural Network Society Apr 20, 2021
In this paper, the bipartite synchronization issue for a class of coupled reaction-diffusion networks with antagonistic interactions and switching topologies is investigated. First of all, by virtue of Lyapunov functional method and pinning control t...
Neural Networks, Computer Computer Simulation Diffusion
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Parallel Binary Image Cryptosystem Via Spiking Neural Networks Variants.

International journal of neural systems Feb 26, 2021
Due to the inefficiency of multiple binary images encryption, a parallel binary image encryption framework based on the typical variants of spiking neural networks, spiking neural P (SNP) systems is proposed in this paper. More specifically, the two ...
Neural Networks, Computer Algorithms Diffusion Neurons
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Synchronization of Nonidentical Neural Networks With Unknown Parameters and Diffusion Effects via Robust Adaptive Control Techniques.

IEEE transactions on cybernetics Jan 15, 2021
This paper considers the self-synchronization and tracking synchronization issues for a class of nonidentically coupled neural networks model with unknown parameters and diffusion effects. Using the special structure of neural networks with global Li...
Humans Neural Networks, Computer Algorithms Research Design Brain Models, Neurological Diffusion
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Global Exponential Synchronization of Coupled Delayed Memristive Neural Networks With Reaction-Diffusion Terms via Distributed Pinning Controls.

IEEE transactions on neural networks and learning systems Jan 4, 2021
This article presents new theoretical results on global exponential synchronization of nonlinear coupled delayed memristive neural networks with reaction-diffusion terms and Dirichlet boundary conditions. First, a state-dependent memristive neural ne...
Neural Networks, Computer Algorithms Computer Simulation Feedback Diffusion Nonlinear Dynamics
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