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Diffusion

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Impulsive synchronization of stochastic reaction-diffusion neural networks with mixed time delays.

Neural networks : the official journal of the International Neural Network Society
This paper discusses impulsive synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and hybrid time delays. By virtue of inequality techniques, theories of stochastic analysis, linear matrix inequalities...

An artificial nociceptor based on a diffusive memristor.

Nature communications
A nociceptor is a critical and special receptor of a sensory neuron that is able to detect noxious stimulus and provide a rapid warning to the central nervous system to start the motor response in the human body and humanoid robotics. It differs from...

Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentiall...

Mittag-Leffler synchronization of fractional neural networks with time-varying delays and reaction-diffusion terms using impulsive and linear controllers.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a fractional-order neural network system with time-varying delays and reaction-diffusion terms. We first develop a new Mittag-Leffler synchronization strategy for the controlled nodes via impulsive controllers. Using the fra...

Synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and unbounded delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and unbounded discrete time-varying delays is investigated. By virtue of theories of partial differential equations, inequality methods...

State Estimation for Delayed Genetic Regulatory Networks With Reaction-Diffusion Terms.

IEEE transactions on neural networks and learning systems
This paper addresses the problem of state estimation for delayed genetic regulatory networks (DGRNs) with reaction-diffusion terms using Dirichlet boundary conditions. The nonlinear regulation function of DGRNs is assumed to exhibit the Hill form. Th...

Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control.

Neural networks : the official journal of the International Neural Network Society
This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are c...

Combined inverse-forward artificial neural networks for fast and accurate estimation of the diffusion coefficients of cartilage based on multi-physics models.

Journal of biomechanics
Analytical and numerical methods have been used to extract essential engineering parameters such as elastic modulus, Poisson׳s ratio, permeability and diffusion coefficient from experimental data in various types of biological tissues. The major limi...

Automatic detection of diffusion modes within biological membranes using back-propagation neural network.

BMC bioinformatics
BACKGROUND: Single particle tracking (SPT) is nowadays one of the most popular technique to probe spatio-temporal dynamics of proteins diffusing within the plasma membrane. Indeed membrane components of eukaryotic cells are very dynamic molecules and...

Liver vessel segmentation based on extreme learning machine.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Liver-vessel segmentation plays an important role in vessel structure analysis for liver surgical planning. This paper presents a liver-vessel segmentation method based on extreme learning machine (ELM). Firstly, an anisotropic filter is used to remo...