Results 21 to 30 of about 246,146 (289)
Research on deconvolution methods for thermal network of power devices
机车电传动, 2023 The structure function method is critical for obtaining Cauer thermal network models for power devices. However, in its deconvolution step, different calculation methods have a large impact on the results, which affects the accuracy of the thermal ...
DENG Erping +5 more
doaj
Prediction of extreme cargo ship panel stresses by using deconvolution
Frontiers in Mechanical Engineering, 2022 Extreme value predictions typically originate from certain functional classes of statistical distributions to fit the data and are subsequently extrapolated.
Oleg Gaidai, Ping Yan, Yihan Xing
doaj +1 more source
Molecules, 2022 Gas chromatography/mass spectrometry (GC/MS) is a long-standing technique for the analysis of volatile organic compounds (VOCs). When coupled with the Ion Analytics software, GC/MS provides unmatched selectivity in the analysis of complex mixtures and it
Scott C. Frost +3 more
doaj +1 more source
Frontiers in Neuroscience, 2017 Psychophysiological interaction (PPI) is a regression based method to study task modulated brain connectivity. Despite its popularity in functional MRI (fMRI) studies, its reliability and reproducibility have not been evaluated.
Xin Di, Bharat B. Biswal
doaj +1 more source
Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM [PDF]
, 2013 We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known.
Almeida +39 more
core +5 more sources
Evaluation and Interpretation of Transcriptome Data Underlying Heterogeneous Chronic Obstructive Pulmonary Disease [PDF]
Genomics & Informatics, 2019 Chronic obstructive pulmonary disease (COPD) is a type of progressive lung disease, featured by airflow obstruction. Recently, a comprehensive analysis of the transcriptome in lung tissue of COPD patients was performed, but the heterogeneity of the ...
Seokjin Ham, Yeon-Mok Oh, Tae-Young Roh
doaj +1 more source
Rapid deconvolution of low-resolution time-of-flight data using Bayesian inference [PDF]
, 2019 The deconvolution of low-resolution time-of-flight data has numerous advantages, including the ability to extract additional information from the experimental data.
Bernardo J. M. +7 more
core +2 more sources
SPIE Proceedings, 2012 In this paper we present a new approach to deblur the effect of atmospheric turbulence in the case of long range imaging. Our method is based on an analytical formulation, the Fried kernel, of the atmosphere modulation transfer function (MTF) and a framelet based deconvolution algorithm.
Jérôme Gilles, Stanley J. Osher
openaire +2 more sources
地球与行星物理论评, 2022 Studying the structures, properties and origins of the Earth's internal discontinuities is an important part in the efforts to understand the physical and chemical properties of the layered Earth, as well as to explore the dynamic processes and driving ...
Ling Chen +4 more
doaj +1 more source
A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping
, 2016 The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smooth \ell_1/\ell_2 regularization term. As the mean of the noise in
Mars, Jérôme I. +3 more
core +3 more sources