AIMC Topic: Neural Networks, Computer

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Modeling Disease Progression via Multisource Multitask Learners: A Case Study With Alzheimer's Disease.

IEEE transactions on neural networks and learning systems
Understanding the progression of chronic diseases can empower the sufferers in taking proactive care. To predict the disease status in the future time points, various machine learning approaches have been proposed. However, a few of them jointly cons...

Determination of the mechanical and physical properties of cartilage by coupling poroelastic-based finite element models of indentation with artificial neural networks.

Journal of biomechanics
One of the most widely used techniques to determine the mechanical properties of cartilage is based on indentation tests and interpretation of the obtained force-time or displacement-time data. In the current computational approaches, one needs to si...

A multi-layer network approach to MEG connectivity analysis.

NeuroImage
Recent years have shown the critical importance of inter-regional neural network connectivity in supporting healthy brain function. Such connectivity is measurable using neuroimaging techniques such as MEG, however the richness of the electrophysiolo...

A Model for Improving the Learning Curves of Artificial Neural Networks.

PloS one
In this article, the performance of a hybrid artificial neural network (i.e. scale-free and small-world) was analyzed and its learning curve compared to three other topologies: random, scale-free and small-world, as well as to the chemotaxis neural n...

Optimizing Semantic Pointer Representations for Symbol-Like Processing in Spiking Neural Networks.

PloS one
The Semantic Pointer Architecture (SPA) is a proposal of specifying the computations and architectural elements needed to account for cognitive functions. By means of the Neural Engineering Framework (NEF) this proposal can be realized in a spiking n...

Design of a heart rate controller for treadmill exercise using a recurrent fuzzy neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In this study, we developed a computer controlled treadmill system using a recurrent fuzzy neural network heart rate controller (RFNNHRC). Treadmill speeds and inclines were controlled by corresponding control servo motors. ...

Noise further expresses exponential decay for globally exponentially stable time-varying delayed neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper shows that the globally exponentially stable neural network with time-varying delay and bounded noises may converge faster than those without noise. And the influence of noise on global exponential stability of DNNs was analyzed quantitati...

Early detection of germinated wheat grains using terahertz image and chemometrics.

Scientific reports
In this paper, we propose a feasible tool that uses a terahertz (THz) imaging system for identifying wheat grains at different stages of germination. The THz spectra of the main changed components of wheat grains, maltose and starch, which were obtai...

Estimation of NMVOC emissions using artificial neural networks and economical and sustainability indicators as inputs.

Environmental science and pollution research international
This paper describes the development of an artificial neural network (ANN) model based on economical and sustainability indicators for the prediction of annual non-methane volatile organic compounds (NMVOCs) emissions in China for the period 2005-201...

Function approximation in inhibitory networks.

Neural networks : the official journal of the International Neural Network Society
In performance-optimized artificial neural networks, such as convolutional networks, each neuron makes excitatory connections with some of its targets and inhibitory connections with others. In contrast, physiological neurons are typically either exc...