Search results for "Neural"

Ghost stochastic resonance in FitzHugh–Nagumo circuit

2014

International audience; The response of a neural circuit submitted to a bi-chromatic stimulus and corrupted by noise is investigated. In the presence of noise, when the spike firing of the circuit is analysed, a frequency not present at the circuit input appears. For a given range of noise intensities, it is shown that this ghost frequency is almost exclusively present in the interspike interval distribution. This phenomenon is for the first time shown experimentally in a FitzHugh-Nagumo circuit.

Neural Classification of Compost Maturity by Means of the Self-Organising Feature Map Artificial Neural Network and Learning Vector Quantization Algo…

2019

Self-Organising Feature Map (SOFM) neural models and the Learning Vector Quantization (LVQ) algorithm were used to produce a classifier identifying the quality classes of compost, according to the degree of its maturation within a period of time recorded in digital images. Digital images of compost at different stages of maturation were taken in a laboratory. They were used to generate an SOFM neural topological map with centres of concentration of the classified cases. The radial neurons on the map were adequately labelled to represent five suggested quality classes describing the degree of maturation of the composted organic matter. This enabled the creation of a neural separator classify…

Theoretical and experimental study of two discrete coupled Nagumo chains

2001

We analyze front wave (kink and antikink) propagation and pattern formation in a system composed of two coupled discrete Nagumo chains using analytical and numerical methods. In the case of homogeneous interaction among the chains, we show the possibility of the effective control on wave propagation. In addition, physical experiments on electrical chains confirm all theoretical behaviors.

Seizure Prediction Using EEG Channel Selection Method

2022

Seizure prediction using intracranial electroencephalogram (iEEG) is still challenging because of complicated signals in spatial and time domains. Feature selection in the spatial domain (i.e., channel selection) has been largely ignored in this field. Hence, in this paper, a novel approach of iEEG channel selection strategy combined with one-dimensional convolutional neural networks (1D-CNN) was presented for seizure prediction. First, 15-sec and 30-sec iEEG segments with an increasing number of channels (from one channel to all channels) were sequentially fed into 1D-CNN models for training and testing. Then, the channel case with the best classification rate was selected for each partici…

Assessing the Open Trenches in Screening Railway Ground-Borne Vibrations by Means of Artificial Neural Network

2009

Reducing ground borne vibrations in urban areas is a very challenging task in railway transportation. Many mitigation measures can be considered and applied; among these open trenches are very effective. This paper deals with the study of the effect, in terms of reduction of vertical and horizontal displacements and velocities, of the open trenches. 2D FEM simulations have been performed and several open trench configurations have been analysed varying the main geometric features such as width and depth, distance from the rail, thickness of the soil layer over the rigid bedrock, type of the ground, ratio between the depth of the trench, and the thickness of the soil layer. For quantifying t…

Study of the effectiveness of the open trenches in reducing railway ground-borne vibrations: sensitivity analysis of its geometric features using art…

2009

Estimating Programming Exercise Difficulty using Performance Factors Analysis

2020

This Work in Progress Paper studies student and exercise modelling based on pass/fail log data gathered from an introductory programming course. Contemporary education capitalizes on the communications technology and remote study. This can create distance between the teacher and students and the resulting lack of awareness of the difficulties students encounter can lead to low student satisfaction, dropout and poor grades. In many cases, various technological solutions are used to collect individual exercise submissions, but there are little resources for indexing or modelling the exercises in depth. Exercise specific feedback from students may not be easily obtainable either. In the presen…

p73 deficiency results in impaired self renewal and premature neuronal differentiation of mouse neural progenitors independently of p53

2010

10 p.-5 fig.

A “Painful Tic Convulsif” (Trigeminal Neuralgia And Ipsilateral Facial Spasm) Due To Double Neuro-Vascular Impingement: A Case Report.

2011

Neurophysiological Changes After Paired Brain and Spinal Cord Stimulation Coupled With Locomotor Training in Human Spinal Cord Injury

2021

Neurophysiological changes that involve activity-dependent neuroplasticity mechanisms via repeated stimulation and locomotor training are not commonly employed in research even though combination of interventions is a common clinical practice. In this randomized clinical trial, we established neurophysiological changes when transcranial magnetic stimulation (TMS) of the motor cortex was paired with transcutaneous thoracolumbar spinal (transspinal) stimulation in human spinal cord injury (SCI) delivered during locomotor training. We hypothesized that TMS delivered before transspinal (TMS-transspinal) stimulation promotes functional reorganization of spinal networks during stepping. In this p…