AIMC Topic: Neural Networks, Computer

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Multistability of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays.

Neural networks : the official journal of the International Neural Network Society
The problem of coexistence and dynamical behaviors of multiple equilibrium points is addressed for a class of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays. By virtue of th...

GABA diffusion across neuronal columns for efficient sensory tuning.

Biological cybernetics
Synaptic (phasic) lateral inhibition between neuronal columns mediated by GABAergic interneurons is, in general, essential for primary sensory cortices to respond selectively to elemental features. We propose here a neural network model with a nonsyn...

Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig.

Computational intelligence and neuroscience
Nowadays the neuroscientific community is taking more and more advantage of the continuous interaction between engineers and computational neuroscientists in order to develop neuroprostheses aimed at replacing damaged brain areas with artificial devi...

Multi-scale deep networks and regression forests for direct bi-ventricular volume estimation.

Medical image analysis
Direct estimation of cardiac ventricular volumes has become increasingly popular and important in cardiac function analysis due to its effectiveness and efficiency by avoiding an intermediate segmentation step. However, existing methods rely on eithe...

Finite time stabilization of delayed neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, the problem of finite time stabilization for a class of delayed neural networks (DNNs) is investigated. The general conditions on the feedback control law are provided to ensure the finite time stabilization of DNNs. Then some specific...

Surrogate modeling of deformable joint contact using artificial neural networks.

Medical engineering & physics
Deformable joint contact models can be used to estimate loading conditions for cartilage-cartilage, implant-implant, human-orthotic, and foot-ground interactions. However, contact evaluations are often so expensive computationally that they can be pr...

Modeling of ammonia emission in the USA and EU countries using an artificial neural network approach.

Environmental science and pollution research international
Ammonia emissions at the national level are frequently estimated by applying the emission inventory approach, which includes the use of emission factors, which are difficult and expensive to determine. Emission factors are therefore the subject of es...

High-order neural networks and kernel methods for peptide-MHC binding prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between diff...

Retinal vessel segmentation using multi-scale textons derived from keypoints.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This paper presents a retinal vessel segmentation algorithm which uses a texton dictionary to classify vessel/non-vessel pixels. However, in contrast to previous work where filter parameters are learnt from manually labelled image pixels our filter p...

Matrix measure method for global exponential stability of complex-valued recurrent neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, based on the matrix measure method and the Halanay inequality, global exponential stability problem is investigated for the complex-valued recurrent neural networks with time-varying delays. Without constructing any Lyapunov functions,...