AIMC Topic: Time Factors

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Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.

International journal of neural systems
Effective common spatial pattern (CSP) feature extraction for motor imagery (MI) electroencephalogram (EEG) recordings usually depends on the filter band selection to a large extent. Subband optimization has been suggested to enhance classification a...

Global exponential stability of complex-valued neural networks with both time-varying delays and impulsive effects.

Neural networks : the official journal of the International Neural Network Society
In this paper, the global exponential stability of complex-valued neural networks with both time-varying delays and impulsive effects is discussed. By employing Lyapunov functional method and using matrix inequality technique, several sufficient cond...

q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans.

IEEE transactions on medical imaging
Numerous scientific fields rely on elaborate but partly suboptimal data processing pipelines. An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive microstructure assessment method with a prominent application in neuroima...

tDCS and Robotics on Upper Limb Stroke Rehabilitation: Effect Modification by Stroke Duration and Type of Stroke.

BioMed research international
Objective. The aim of this exploratory pilot study is to test the effects of bilateral tDCS combined with upper extremity robot-assisted therapy (RAT) on stroke survivors. Methods. We enrolled 23 subjects who were allocated to 2 groups: RAT + real tD...

Passivity analysis of uncertain stochastic neural networks with time-varying delays and Markovian jumping parameters.

Network (Bristol, England)
This paper investigates the problem of robust passivity of uncertain stochastic neural networks with time-varying delays and Markovian jumping parameters. To reflect most of the dynamical behaviors of the system, both parameter uncertainties and stoc...

Trends in Robotic-Assisted Coronary Artery Bypass Grafts: A Study of The Society of Thoracic Surgeons Adult Cardiac Surgery Database, 2006 to 2012.

The Annals of thoracic surgery
BACKGROUND: Robotic technology is one of the most recent technological changes in coronary artery bypass graft (CABG) operations. The current analysis was conducted to identify trends in the use and outcomes of robotic-assisted CABG (RA-CABG).

Ubiquitous Multicriteria Clinic Recommendation System.

Journal of medical systems
Advancements in information, communication, and sensor technologies have led to new opportunities in medical care and education. Patients in general prefer visiting the nearest clinic, attempt to avoid waiting for treatment, and have unequal preferen...

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...

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...