Search results for "Conti"
showing 10 items of 3486 documents
EMG artifacts removal during electrical stimulation, a CWT based technique
2014
International audience; A technique of artifacts removal based on the continuous wavelet transform is presented. It uses common mother wavelets to find the temporal localization of stimulation artifacts on electromyogram (EMG) signal during an electrically evoked contraction of a muscle. This method can be used with standard stimulation pulse waveforms like monophasics or biphasics ones. It uses a histogram representation to find the best threshold to apply on the CWT domain. The algotithm is presented with Haar wavelet and then it is used with common wavelet famillies such as Daubechies or Symlets.
The Wavelet Scalogram in the Study of Time Series
2014
Wavelet theory has been proved to be a useful tool in the study of time series. Specifically, the scalogram allows the detection of the most representative scales (or frequencies) of a signal. In this work, we present the scalogram as a tool for studying some aspects of a given signal. Firstly, we introduce a parameter called scale index, interpreted as a measure of the degree of the signal’s non-periodicity. In this way, it can complement the maximal Lyapunov exponent method for determining chaos transitions of a given dynamical system. Secondly, we introduce a method for comparing different scalograms. This can be applied for determining if two time series follow similar patterns.
High-fidelity analysis of multilayered shells with cut-outs via the discontinuous Galerkin method
2021
Abstract A novel numerical method for the analysis of multilayered shells with cut-outs is presented. In the proposed approach, the shell geometry is represented via either analytical functions or NURBS parametrizations , while generally-shaped cut-outs are defined implicitly within the shell modelling domain via a level set function . The multilayered shell problem is addressed via the Equivalent-Single-Layer approach whereby high-order polynomial functions are employed to approximate the covariant components of the displacement field throughout the shell thickness. The shell governing equations are then derived from the Principle of Virtual Displacements of three-dimensional elasticity an…
Enhanced supercontinuum generation in tapered tellurite suspended core fiber
2015
Abstract We demonstrate 400-THz (0.6–3.3 µm) bandwidth infrared supercontinuum generation in a 10 cm-long tapered tellurite suspended core fiber pumped by nJ-level 200-fs pulses from an optical parametric oscillator. The increased nonlinearity and dispersion engineering extended by the moderate reduction of the fiber core size are exploited for supercontinuum optimization on both frequency edges (i.e., 155-THz overall gain), while keeping efficient power coupling into the untapered fiber input. The remaining limitation of supercontinuum bandwidth is related to the presence of the high absorption beyond 3 µm whereas spectral broadening is expected to fully cover the glass transmission window…
Localization and separation of solutions for Fredholm integral equations
2020
[EN] In this paper, we establish a qualitative study of nonlinear Fredholm integral equations, where we will carry out a study on the localization and separation of solutions. Moreover, we consider an efficient algorithm to approximate a solution. To do this, we study the semilocal convergence of an efficient third order iterative scheme for solving nonlinear Fredholm integral equations under mild conditions. The novelty of our work lies in the fact that this study involves first order Frechet derivative and mild conditions. A numerical example involving nonlinear Fredholm integral equations, is solved to show the domains of existence and uniqueness of solutions. The applicability of the it…
Path dependence and landscape: initial conditions, contingency and sequences of events in latgale, latvia
2013
AbstractThe notion of path dependence has not yet been well explored as a tool for analysing landscape change. Within geography it is primarily economic geographers who have, up until now, shown a keen interest in this concept which stresses the role of social agency and institutions in understanding the development trajectories of regions. Further, the notion of path dependence usefully captures the idea of contingency in historical sequences. This article presents such a perspective on landscape change analysis, discussing two dominant types of sequences in path‐dependent systems. Self‐reinforcing sequences characterize the formation and long‐term reproduction of a given institutional pat…
On Fuzzy Stochastic Integral Equations—A Martingale Problem Approach
2011
In the paper we consider fuzzy stochastic integral equations using the methods of stochastic inclusions. The idea is to consider an associated martingale problem and its solutions in order to obtain a solution to the fuzzy stochastic equation.
Non-Contact Measurement of River Surface Velocity and Discharge Estimation with a Low-Cost Doppler Radar Sensor
2020
River discharge is an important variable to measure in order to predict droughts and flood occurrences. Once the cross-sectional geometry of the river is known, discharge can be inferred from water level and surface flow velocity measurements. Since river discharges are of particular interest during extreme weather events, when river sites cannot be safely accessed, noncontact sensing technologies are particularly appealing. To this purpose, this work proposes a prototype of a low-cost continuous wave (CW) Doppler radar sensor, which is able to monitor the surface flow velocity of rivers. The prototype is tested at two gauged sites in central Italy, along the Tiber River. The surface flow v…
Diagnosis of Incipient Bearing Faults using Convolutional Neural Networks
2019
The majority of faults occurring in rotating electrical machinery is attributed to bearings. To reduce downtime, it is desired to apply various diagnostic methods so that bearing degradation can be detected in good time prior to a complete failure. The work presented in this paper utilizes a data-driven machine learning approach based on convolutional neural networks (CNNs) in order to diagnose different types of bearing faults. A one-dimensional CNN is trained on vibration signals and compared to a two-dimensional CNN trained in time-frequency domain using continuous wavelet transform (CWT). The proposed method is demonstrated on data collected from run-to-failure tests.The results show th…
La coexistence du droit civil et du common law en Afrique
2014
L'article analyse le rapport entre common law et droit continental dans le contexte du droit OHADA