AIMC Topic: Neural Networks, Computer

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Sample entropy analysis of EEG signals via artificial neural networks to model patients' consciousness level based on anesthesiologists experience.

BioMed research international
Electroencephalogram (EEG) signals, as it can express the human brain's activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA). Bispectra...

Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well established.

A new class of multi-stable neural networks: stability analysis and learning process.

Neural networks : the official journal of the International Neural Network Society
Recently, multi-stable Neural Networks (NN) with exponential number of attractors have been presented and analyzed theoretically; however, the learning process of the parameters of these systems while considering stability conditions and specificatio...

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...

Size Control in the Nanoprecipitation Process of Stable Iodine (¹²⁷I) Using Microchannel Reactor-Optimization by Artificial Neural Networks.

AAPS PharmSciTech
In this study, nanosuspension of stable iodine ((127)I) was prepared by nanoprecipitation process in microfluidic devices. Then, size of particles was optimized using artificial neural networks (ANNs) modeling. The size of prepared particles was eval...

Bayes optimal template matching for spike sorting - combining fisher discriminant analysis with optimal filtering.

Journal of computational neuroscience
Spike sorting, i.e., the separation of the firing activity of different neurons from extracellular measurements, is a crucial but often error-prone step in the analysis of neuronal responses. Usually, three different problems have to be solved: the d...

A framework for final drive simultaneous failure diagnosis based on fuzzy entropy and sparse bayesian extreme learning machine.

Computational intelligence and neuroscience
This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction ...

Adaptive Neural Control of a Class of Output-Constrained Nonaffine Systems.

IEEE transactions on cybernetics
In this paper, we present a novel tracking controller for a class of uncertain nonaffine systems with time-varying asymmetric output constraints. Firstly, the original nonaffine constrained (in the sense of the output signal) control system is transf...

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 ...