Search results for "Signal processing"
showing 10 items of 2451 documents
Wiener-Granger Causality in Network Physiology with Applications to Cardiovascular Control and Neuroscience
2016
Since the operative definition given by C. W. J. Granger of an idea expressed by N. Wiener, the Wiener–Granger causality (WGC) has been one of the most relevant concepts exploited by modern time series analysis. Indeed, in networks formed by multiple components, working according to the notion of segregation and interacting with each other according to the principle of integration, inferring causality has opened a window on the effective connectivity of the network and has linked experimental evidences to functions and mechanisms. This tutorial reviews predictability improvement, information-based and frequency domain methods for inferring WGC among physiological processes from multivariate…
The relevance of point defects in studying silica-based materials from bulk to nanosystems
2019
The macroscopic properties of silica can be modified by the presence of local microscopic modifications at the scale of the basic molecular units (point defects). Such defects can be generated during the production of glass, devices, or by the environments where the latter have to operate, impacting on the devices’ performance. For these reasons, the identification of defects, their generation processes, and the knowledge of their electrical and optical features are relevant for microelectronics and optoelectronics. The aim of this manuscript is to report some examples of how defects can be generated, how they can impact device performance, and how a defect species or a physical phenomenon …
Increasing stability in the linearized inverse Schrödinger potential problem with power type nonlinearities
2022
We consider increasing stability in the inverse Schr\"{o}dinger potential problem with power type nonlinearities at a large wavenumber. Two linearization approaches, with respect to small boundary data and small potential function, are proposed and their performance on the inverse Schr\"{o}dinger potential problem is investigated. It can be observed that higher order linearization for small boundary data can provide an increasing stability for an arbitrary power type nonlinearity term if the wavenumber is chosen large. Meanwhile, linearization with respect to the potential function leads to increasing stability for a quadratic nonlinearity term, which highlights the advantage of nonlinearit…
Measurement of the average shape of longitudinal profiles of cosmic-ray air showers at the Pierre Auger Observatory
2019
The profile of the longitudinal development of showers produced by ultra-high energy cosmic rays carries information related to the interaction properties of the primary particles with atmospheric nuclei. In this work, we present the first measurement of the average shower profile in traversed atmospheric depth at the Pierre Auger Observatory. The shapes of profiles are well reproduced by the Gaisser-Hillas parametrization within the range studied, for E>10 17.8 eV .A detailed analysis of the systematic uncertainties is performed using ten years of data and a full detector simulation. The average shape is quantified using two variables related to the width and asymmetry of the profile, and …
Enabling Energy Savings in Offshore Mechatronic Systems by using Self-Contained Cylinders
2019
This paper proposes a novel actuation system for an offshore drilling application. It consists of three self-contained electro-hydraulic cylinders that can share and store regenerated energy. The energy saving potential of the proposed solution is analyzed through a multibody system simulation. The self-contained system demonstrates superior energy efficiency compared to the benchmark system representing the state-of-the-art approach used today (i.e., valve-controlled cylinders by means of pressure-compensated directional control valves and counter-balance valves, supplied by a centralized hydraulic power unit). Due to the power on demand capability, the cancellation of the throttling losse…
Single Event Upsets Induced by Direct Ionization from Low-Energy Protons in Floating Gate Cells
2017
Floating gate cells in advanced NAND Flash memories, with single-level and multi-level cell architecture, were exposed to low-energy proton beams. The first experimental evidence of single event upsets by proton direct ionization in floating gate cells is reported. The dependence of the error rate versus proton energy is analyzed in a wide energy range. Proton direct ionization events are studied and energy loss in the overlayers is discussed. The threshold LET for floating gate errors in multi-level and single-level cell devices is modeled and technology scaling trends are analyzed, also discussing the impact of the particle track size. peerReviewed
Novel qutrit circuit design for multiplexer, De-multiplexer, and decoder
2022
AbstractDesigning conventional circuits present many challenges, including minimizing internal power dissipation. An approach to overcoming this problem is utilizing quantum technology, which has attracted significant attention as an alternative to Nanoscale CMOS technology. The reduction of energy dissipation makes quantum circuits an up-and-coming emerging technology. Ternary logic can potentially diminish the quantum circuit width, which is currently a limitation in quantum technologies. Using qutrit instead of qubit could play an essential role in the future of quantum computing. First, we propose two approaches for quantum ternary decoder circuit in this context. Then, we propose a qua…
Fault diagnosis of induction motors broken rotor bars by pattern recognition based on noise cancelation
2014
Current signal monitoring (CSM) can be used as an effective tool for diagnosing broken rotor bars fault in induction motors. In this paper, fault diagnosis and classification based on artificial neural networks (ANNs) is done in two stages. In the first stage, a filter is designed to remove irrelevant fault components (such as noise) of current signals. The coefficients of the filter are obtained by least square (LS) algorithm. Then by extracting suitable time domain features from filter's output, a neural network is trained for fault classification. The output vector of this network is represented in one of four categories that includes healthy mode, a 5 mm crack on a bar, one broken bar, …
Deep-learning based reconstruction of the shower maximum X max using the water-Cherenkov detectors of the Pierre Auger Observatory
2021
The atmospheric depth of the air shower maximum $X_{\mathrm{max}}$ is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of $X_{\mathrm{max}}$ are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of $X_{\mathrm{max}}$ from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of $X_{\mathrm{max}}$. The reconstruction relies on the signals induced by shower particles in the groun…
SingleChannelNet : A model for automatic sleep stage classification with raw single-channel EEG
2022
In diagnosing sleep disorders, sleep stage classification is a very essential yet time-consuming process. Various existing state-of-the-art approaches rely on hand-crafted features and multi-modality polysomnography (PSG) data, where prior knowledge is compulsory and high computation cost can be expected. Besides, it is a big challenge to handle the task with raw single-channel electroencephalogram (EEG). To overcome these shortcomings, this paper proposes an end-to-end framework with a deep neural network, namely SingleChannelNet, for automatic sleep stage classification based on raw single-channel EEG. The proposed model utilizes a 90s epoch as the textual input and employs two multi-conv…