Search results for " NEURAL NETWORKS"
showing 10 items of 390 documents
From orientational glasses to structural glasses: What computer simulations have contributed to understand experiments
2002
Abstract Orientational glasses, produced by random dilution of molecular crystals, exhibit a freezing transition of the quadrupole moments. Monte Carlo simulations of lattice models (generalization of the Edwards–Anderson spin glass model) have been used to elucidate this behavior. While short range models exhibit a static glass transition at zero temperature only, the infinite range Potts glass exhibits a transition where a glass order parameter appears discontinuously. At higher temperature, a dynamical transition occurs, described by mode-coupling theory (MCT). MCT has also been tested by Monte Carlo and molecular dynamics simulations of coarse-grained models of glass-forming polymers. W…
One and Two Dimensional Convolutional Neural Networks for Seizure Detection Using EEG Signals
2021
Deep learning for the automated detection of epileptic seizures has received much attention during recent years. In this work, one dimensional convolutional neural network (1D-CNN) and two dimensional convolutional neural network (2D-CNN) are simultaneously used on electroencephalogram (EEG) data for seizure detection. Firstly, using sliding windows without overlap on raw EEG to obtain the definite one-dimension time EEG segments (1D-T), and continuous wavelet transform (CWT) for 1D-T signals to obtain the two-dimension time-frequency representations (2D-TF). Then, 1D-CNN and 2D-CNN model architectures are used on 1D-T and 2D-TF signals for automatic classification, respectively. Finally, t…
Computational Modeling of Human Visual Function using Psychophysics, Deep Neural Networks, and Information Theory
2023
Visual perception is a key to unlocking the secrets of brain functions because most of the information is processed through the early visual system and then transmitted to the high-level cognitive perception brain regions. The brain functions as a self-organizing, bio-dynamic, and chaotic system that receives outside information and then decomposes it into pieces of information that can be processed efficiently and independently. The work connects natural image statistics, psychophysics, deep neural networks, and information theory to perceptual vision systems to explore how vision processes information from the outside world and how the information coupled drives functional connectivity be…
Nonlinear Relaxation in Population Dynamics
2001
We analyze the nonlinear relaxation of a complex ecosystem composed of many interacting species. The ecological system is described by generalized Lotka-Volterra equations with a multiplicative noise. The transient dynamics is studied in the framework of the mean field theory and with random interaction between the species. We focus on the statistical properties of the asymptotic behaviour of the time integral of the i-th population and on the distribution of the population and of the local field.
Characterization of E'delta and triplet point defects in oxygen-deficient amorphous silicon dioxide
2005
We report an experimental study by electron paramagnetic resonance (EPR) of gamma ray irradiation induced point defects in oxygen deficient amorphous SiO2 materials. We have found that three intrinsic (E'gamma, E'delta and triplet) and one extrinsic ([AlO4]0) paramagnetic centers are induced. All the paramagnetic defects but E'gamma center are found to reach a concentration limit value for doses above 10^3 kGy, suggesting a generation process from precursors. Isochronal thermal treatments of a sample irradiated at 10^3 kGy have shown that for T>500 K the concentrations of E'gamma and E'delta centers increase concomitantly to the decrease of [AlO4]0. This occurrence speaks for an hole tra…
One Dimensional Convolutional Neural Networks for Seizure Onset Detection Using Long-term Scalp and Intracranial EEG
2021
Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial electroencephalogram (iEEG) has attracted widespread attention in recent two decades. The accurate and rapid detection of seizures not only reflects the efficiency of the algorithm, but also greatly reduces the burden of manual detection during long-term electroencephalogram (EEG) recording. In this work, a stacked one-dimensional convolutional neural network (1D-CNN) model combined with a random selection and data augmentation (RS-DA) strategy is proposed for seizure onset detection. Firstly, we segmented the long-term EEG signals using 2-sec sliding windows. Then, the 2-sec interictal and ictal segments w…
Convolutional Neural Network Based Sleep Stage Classification with Class Imbalance
2022
Accurate sleep stage classification is vital to assess sleep quality and diagnose sleep disorders. Numerous deep learning based models have been designed for accomplishing this labor automatically. However, the class imbalance problem existing in polysomnography (PSG) datasets has been barely investigated in previous studies, which is one of the most challenging obstacles for the real-world sleep staging application. To address this issue, this paper proposes novel methods with signal-driven and image-driven ways of noise addition to balance the imbalanced relationship in the training dataset samples. We evaluate the effectiveness of the proposed methods which are integrated into a convolut…
A Navigation and Augmented Reality System for Visually Impaired People
2021
In recent years, we have assisted with an impressive advance in augmented reality systems and computer vision algorithms, based on image processing and artificial intelligence. Thanks to these technologies, mainstream smartphones are able to estimate their own motion in 3D space with high accuracy. In this paper, we exploit such technologies to support the autonomous mobility of people with visual disabilities, identifying pre-defined virtual paths and providing context information, reducing the distance between the digital and real worlds. In particular, we present ARIANNA+, an extension of ARIANNA, a system explicitly designed for visually impaired people for indoor and outdoor localizati…
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…