Search results for "noise reduction"
showing 10 items of 71 documents
DC and 1/f noise characterization of cryogenically cooled pseudomorphic HEMT's
2002
Pseudomorphic (AlGaAs/InGaAs/GaAs) HEMT's have exhibited the best noise performance over the entire LF-to-microwave frequency range if compared to MESFET's and conventional GaAs HEMT's, due to either a reduced flicker noise, a lower G/R contribution and a smaller high-field diffusion noise. We have recently investigated the microwave (up to 18 GHz) noise properties of packaged pseudomorphic HEMT's from 290 K down to cryogenic temperature values. The current experimental work is aimed at extending such analysis to the LF noise range and at low temperatures. Cryogenic noise spectra (1 Hz to 100 KHz) and DC characteristics have therefore been recorded and the relevant observations on the devic…
Subsignal-based denoising from piecewise linear or constant signal
2011
15 pages; International audience; n the present work, a novel signal denoising technique for piecewise constant or linear signals is presented termed as "signal split." The proposed method separates the sharp edges or transitions from the noise elements by splitting the signal into different parts. Unlike many noise removal techniques, the method works only in the nonorthogonal domain. The new method utilizes Stein unbiased risk estimate (SURE) to split the signal, Lipschitz exponents to identify noise elements, and a polynomial fitting approach for the sub signal reconstruction. At the final stage, merging of all parts yield in the fully denoised signal at a very low computational cost. St…
Non Linear Image Restoration in Spatial Domain
2011
International audience; In the present work, a novel image restoration method from noisy data samples is presented. The restoration was per-formed by using some heuristic approach utilizing data samples and smoothness criteria in spatial domain. Unlike most existing techniques, this approach does not require prior modelling of either the image or noise statistics. The proposed method works in an interactive mode to find the best compromise between the data (mean square error) and the smoothing criteria. The method has been compared with the shrinkage approach, Wiener filter and Non Local Means algorithm as well. Experimental results showed that the proposed method gives better signal to noi…
Moisture absorption, thermal conductivity and noise mitigation of clay based plasters: The influence of mineralogical and textural characteristics
2016
Abstract Three pre-mixed clay based plasters successfully employed in green building practices in several European countries (Spain, France, Germany, and United Kingdom), mainly used for interior wall coating and finishing, were tested in this paper. Their compositional and textural characteristics as well as plastic behaviour were investigated through a multi-analytical approach in a previous paper. A natural earth (Terra Rossa red soil sampled in north-western Sicily), theoretically appropriate for the production of earthen plaster, was also subjected to the same analytical routine and compared with the three commercially available products. Humidity control capacity by the determination …
Impulse noise removal on an embedded, low memory SIMD processor
2003
Vector median filters efficiently reduce noise while preserving image details. However, their high computational complexity for color images makes them impractical for real-time systems. We propose new computationally efficient filtering algorithms, called index mapping filters (IMF). These filtering algorithms are accelerated by implementing them on a massively data parallel processor array. In addition to greater computational efficiency, these algorithms result in robust noise reduction of corrupted color images. Analyses of mean square error, signal-to-noise-ratio, and visual comparison metrics indicate that IMF are competitive with the vector median filter (VMF) in their ability to cor…
Signal Denoising with Harten’s Multiresolution Using Interpolation and Least Squares Fitting
2014
Harten’s multiresolution has been successfully applied to the signal compression using interpolatory reconstructions with nonlinear techniques. Here we study the applicability of these techniques to remove noise to piecewise smooth signals. We use two reconstruction types: interpolatory and least squares, and we introduce ENO and SR nonlinear techniques. The standard methods adaptation to noisy signals and the comparative of the different schemes are the subject of this paper.
Classification of gravitational-wave glitches via dictionary learning
2018
We present a new method for the classification of transient noise signals (or glitches) in advanced gravitational-wave interferometers. The method uses learned dictionaries (a supervised machine learning algorithm) for signal denoising, and untrained dictionaries for the final sparse reconstruction and classification. We use a data set of 3000 simulated glitches of three different waveform morphologies, comprising 1000 glitches per morphology. These data are embedded in non-white Gaussian noise to simulate the background noise of advanced LIGO in its broadband configuration. Our classification method yields a 96% accuracy for a large range of initial parameters, showing that learned diction…
Sound absorption prediction of linear damped acoustic resonators using a lightweight hybrid model
2019
International audience; A lightweight numerical method is developed to predict the sound absorption coefficient of resonators whose cross-section dimensions are significantly larger compared to the viscous and thermal boundary layer’s thicknesses. This method is based on the boundary layer theory and on the perturbations theory. According to the perturbations theory, in acoustical domains with large dimensions, the fluid viscosity and thermal conductivity only affect the boundary layers. The model proposed in this article combines the lossless Helmholtz wave equation derived from a perfect fluid hypothesis, with viscosity and thermal conductivity values of a real fluid to compute the sound …
Total-variation methods for gravitational-wave denoising: Performance tests on Advanced LIGO data
2018
We assess total-variation methods to denoise gravitational-wave signals in real noise conditions, by injecting numerical-relativity waveforms from core-collapse supernovae and binary black hole mergers in data from the first observing run of Advanced LIGO. This work is an extension of our previous investigation where only Gaussian noise was used. Since the quality of the results depends on the regularization parameter of the model, we perform an heuristic search for the value that produces the best results. We discuss various approaches for the selection of this parameter, either based on the optimal, mean, or multiple values, and compare the results of the denoising upon these choices. Mor…
Monte Carlo Study of Diffusion Noise Reduction in GaAs Operating under Periodic Conditions
2009
The effects of an external correlated source of noise on the intrinsic carrier noise in a low‐doped GaAs bulk, operating under periodic conditions, are investigated. Numerical results confirm that the dynamical response of electrons driven by a high‐frequency periodic electric field receives a benefit by the constructive interplay between the fluctuating field and the intrinsic noise of the system. In particular, in this contribute we show a nonmonotonic behavior of the integrated spectral density, which value critically depends on the correlation time of the external noise source.