AIMC Topic: Time Factors

Clear Filters Showing 1641 to 1650 of 2001 articles

Automated classification of neurological disorders of gait using spatio-temporal gait parameters.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
OBJECTIVE: Automated pattern recognition systems have been used for accurate identification of neurological conditions as well as the evaluation of the treatment outcomes. This study aims to determine the accuracy of diagnoses of (oto-)neurological g...

Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model.

Physiological measurement
Seizures below one minute in duration are difficult to assess correctly using seizure detection algorithms. We aimed to improve neonatal detection algorithm performance for short seizures through the use of trend templates for seizure onset and end. ...

Prediction of HPLC retention times of tebipenem pivoxyl and its degradation products in solid state by applying adaptive artificial neural network with recursive features elimination.

Talanta
A sensitive and fast HPLC method using ultraviolet diode-array detector (DAD)/electrospray ionization tandem mass spectrometry (Q-TOF-MS/MS) was developed for the determination of tebipenem pivoxyl and in the presence of degradation products formed d...

pth moment exponential stochastic synchronization of coupled memristor-based neural networks with mixed delays via delayed impulsive control.

Neural networks : the official journal of the International Neural Network Society
This paper concerns the pth moment synchronization in an array of generally coupled memristor-based neural networks with time-varying discrete delays, unbounded distributed delays, as well as stochastic perturbations. Hybrid controllers are designed ...

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

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the problem of coexistence and dynamical behaviors of multiple equilibrium points for neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. The fixed point theorem...

16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.

PloS one
The diversity of microbial species in a metagenomic study is commonly assessed using 16S rRNA gene sequencing. With the rapid developments in genome sequencing technologies, the focus has shifted towards the sequencing of hypervariable regions of 16S...

Spatiotemporal System Identification With Continuous Spatial Maps and Sparse Estimation.

IEEE transactions on neural networks and learning systems
We present a framework for the identification of spatiotemporal linear dynamical systems. We use a state-space model representation that has the following attributes: 1) the number of spatial observation locations are decoupled from the model order; ...

The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning.

Nature communications
The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to...

Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays.

IEEE transactions on neural networks and learning systems
This paper investigates the stochastic synchronization problem for Markovian hybrid coupled neural networks with interval time-varying mode-delays and random coupling strengths. The coupling strengths are mutually independent random variables and the...

C1-almost periodic solutions of BAM neural networks with time-varying delays on time scales.

TheScientificWorldJournal
On a new type of almost periodic time scales, a class of BAM neural networks is considered. By employing a fixed point theorem and differential inequality techniques, some sufficient conditions ensuring the existence and global exponential stability ...