Search results for "Gaussian function"
showing 10 items of 21 documents
Stochastic differential calculus for wind-exposed structures with autoregressive continuous (ARC) filters
2008
In this paper, an alternative method to represent Gaussian stationary processes describing wind velocity fluctuations is introduced. The technique may be considered the extension to a time continuous description of the well-known discrete-time autoregressive model to generate Gaussian processes. Digital simulation of Gaussian random processes with assigned auto-correlation function is provided by means of a stochastic differential equation with time delayed terms forced by Gaussian white noise. Solution of the differential equation is a specific sample of the target Gaussian wind process, and in this paper it describes a digitally obtained record of the wind turbolence. The representation o…
Numerical and experimental verification of a technique for locating a fatigue crack on beams vibrating under Gaussian excitation
2007
The stationary vibrations of a beam excited by Gaussian noise are strongly affected by the presence of a fatigue crack. Indeed, as soon as the crack arises the system response becomes non-linear due to crack breathing and a non-Gaussian behaviour is encountered. The paper presents both numerical and experimental investigations in order to assess the capability of the non-Gaussianity measures to detect crack presence and position. Monte Carlo method is applied to evaluate in time domain the higher order statistics of a cantilever beam modelled by finite elements. The skewness coefficient of the rotational degrees of freedom appears the most suitable quantity for identification purpose being …
Peak deconvolution in one-dimensional chromatography using a two-way data approach.
2002
A deconvolution methodology for overlapped chromatographic signals is proposed. Several single-wavelength chromatograms of binary mixtures, obtained in different runs at diverse concentration ratios of the individual components, were simultaneously processed (multi-batch approach), after being arranged as two-way data. The chromatograms were modelled as linear combinations of forced peak profiles according to a polynomially modified Gaussian equation. The fitting was performed with a previously reported hybrid genetic algorithm with local search, leaving all model parameters free. The approach yielded more accurate solutions than those found when each experimental chromatogram was fitted in…
Highlighting numerical insights of an efficient SPH method
2018
Abstract In this paper we focus on two sources of enhancement in accuracy and computational demanding in approximating a function and its derivatives by means of the Smoothed Particle Hydrodynamics method. The approximating power of the standard method is perceived to be poor and improvements can be gained making use of the Taylor series expansion of the kernel approximation of the function and its derivatives. The modified formulation is appealing providing more accurate results of the function and its derivatives simultaneously without changing the kernel function adopted in the computation. The request for greater accuracy needs kernel function derivatives with order up to the desidered …
Towards an Efficient Implementation of an Accurate SPH Method
2020
A modified version of the Smoothed Particle Hydrodynamics (SPH) method is considered in order to overcome the loss of accuracy of the standard formulation. The summation of Gaussian kernel functions is employed, using the Improved Fast Gauss Transform (IFGT) to reduce the computational cost, while tuning the desired accuracy in the SPH method. This technique, coupled with an algorithmic design for exploiting the performance of Graphics Processing Units (GPUs), makes the method promising, as shown by numerical experiments.
Optimal Filter Estimation for Lucas-Kanade Optical Flow
2012
Optical flow algorithms offer a way to estimate motion from a sequence of images. The computation of optical flow plays a key-role in several computer vision applications, including motion detection and segmentation, frame interpolation, three-dimensional scene reconstruction, robot navigation and video compression. In the case of gradient based optical flow implementation, the pre-filtering step plays a vital role, not only for accurate computation of optical flow, but also for the improvement of performance. Generally, in optical flow computation, filtering is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image filt…
Instantaneous distribution of global and diffuse radiation on horizontal surfaces
1991
Abstract The aim of this paper is to obtain a general expression for estimating both the instantaneous global and diffuse radiations on horizontal surfaces from the respective daily values. The proposed expression is a modified Gaussian distribution with two parameters which take into account its width and the asymmetries between morning and afternoon hours. The performance of the method has been tested by comparing the theoretical hourly results with the experimental data of six actinometric stations with different geographical location and climatic conditions. The comparison has shown that the method here proposed is accurate for both the diffuse and global radiation.
Distributed Learning Automata-based S-learning scheme for classification
2019
This paper proposes a novel classifier based on the theory of Learning Automata (LA), reckoned to as PolyLA. The essence of our scheme is to search for a separator in the feature space by imposing an LA-based random walk in a grid system. To each node in the grid, we attach an LA whose actions are the choices of the edges forming a separator. The walk is self-enclosing, and a new random walk is started whenever the walker returns to the starting node forming a closed classification path yielding a many-edged polygon. In our approach, the different LA attached to the different nodes search for a polygon that best encircles and separates each class. Based on the obtained polygons, we perform …
Beam test results of IHEP-NDL Low Gain Avalanche Detectors(LGAD)
2020
A High-Granularity Timing Detector (HGTD) is proposed based on the Low-Gain Avalanche Detector (LGAD) for the ATLAS experiment to satisfy the time resolution requirement for the up-coming High Luminosity at LHC (HL-LHC). We report on beam test results for two proto-types LGADs (BV60 and BV170) developed for the HGTD. Such modules were manufactured by the Institute of High Energy Physics (IHEP) of Chinese Academy of Sciences (CAS) collaborated with Novel Device Laboratory (NDL) of the Beijing Normal University. The beam tests were performed with 5 GeV electron beam at DESY. The timing performance of the LGADs was compared to a trigger counter consisting of a quartz bar coupled to a SiPM read…
A Mixed Approach for Determination of Initial Cable Forces in Cable-Stayed Bridges and the Parameters Variability
2015
The determination of initial cable forces in cable-stayed bridges is an important first step in design and analysis of the structure under external loads. Adjustments of stay forces are often required during construction in order to assure the requested behaviour of the bridge in terms of final geometrical configuration and internal force distribution. An accurate assessment of the stay tensioning system allows designers to obtain a good result at the end of construction, by considering the parameters involved as deterministic quantities, assuring the observance of the execution tolerances during works. Actual loads and their variations need instead a stochastic approach which can give usef…