用于电介质中空间电荷分布测量的Tikhonov反卷积算法

研究了使用压力波法测量平板电介质试样的空间电荷分布的数值解法,使用基于Tikhonov正则化方法的反卷积算法得到了真实的空间电荷分布.在反卷积算法中使用了相关的技术处理,如小波包过滤高频噪音,Tikhonov正则化方法处理积分方程等.利用数值实验研究了噪声对反卷积算法的影响,结果表明,在无噪或者低噪环境下,反卷积算法能够非常好地计算出电介质中的空间电荷分布;在处理有噪数据时,反卷积的结果受到明显的影响,但仍然有较高的计算精度.正则化参数α对空间电荷分布的数值解起着明显的光滑作用,但是对于解的积分值却影响不大.对实际测量数据进行处理的结果表明,反卷积算法成功地计算出了固体电介质中的空间电荷分布和电场分布.     

Deconvolution‐based nonlinear filtering for incompressible flows at moderately large Reynolds numbers

We consider a Leray model with a deconvolution‐based indicator function for the simulation of incompressible fluid flow at moderately large Reynolds number (in the range of a few thousands) with under‐resolved meshes. For the implementation of the model, we adopt a three‐step algorithm called evolve–filter–relax that requires (i) the solution of a Navier–Stokes problem, (ii) the solution of a Stokes‐like problem to filter the Navier–Stokes velocity field, and (iii) a final relaxation step. We take advantage of a reformulation of the evolve–filter–relax algorithm as an operator‐splitting method to analyze the impact of the filter on the final solution versus a direct simulation of the Navier–Stokes equations. In addition, we provide some direction for tuning the parameters involved in the model based on physical and numerical arguments. Our approach is validated against experimental data for fluid flow in an idealized medical device (consisting of a conical convergent, a narrow throat, and a sudden expansion, as recommended by the U.S. Food and Drug Administration). Numerical results are in good quantitative agreement with the measured axial components of the velocity and pressures for two different flow rates corresponding to turbulent regimes, even for meshes with a mesh size more than 40 times larger than the smallest turbulent scale. After several numerical experiments, we perform a preliminary sensitivity analysis of the computed solution to the parameters involved in the model. Copyright © 2015 John Wiley & Sons, Ltd.     

Two-stage blind deconvolution scheme using useful priors

Hand shake blurry image is a common phenomenon in our daily life. In this paper, a novel blind deconvolution scheme is proposed to recover a single hand shake blurry image. The algorithm is subdivided into two main stages, kernel estimation stage and non-blind deconvolution stage. In the kernel estimation stage, we propose a cost function taking a selected map into consideration. In the non-blind decovolution stage, another cost function is designed using image derivatives prior. We also present an adaptive kernel size selection method instead of traditional manual selection. Extensive experiments on real world blurry images are conducted to demonstrate the performance of our algorithm.     

Technical and practical aspects of 19F NMR‐based screening: toward sensitive high‐throughput screening with rapid deconvolution

The technical and practical aspects of ¹⁹F NMR‐based screening against a macromolecular target are analyzed in detail. A novel method utilizing the relaxation of ¹⁹F homonuclear double quantum coherence is proposed for performing NMR‐based binding assays in a direct‐ or competition‐mode format. A combined strategy based on ¹⁹F NMR chemical shift prediction, 2D ¹⁹F NMR DOSY, and 2D ¹⁹F–¹H NMR long‐range COSY experiments is presented for the deconvolution of complex mixtures of fluorinated molecules generated by either addition of single compounds or by chemical synthesis. The approaches presented here allow the screening of complex mixtures, even in the case where the exact composition is not known, and the rapid identification of the binders contained in the mixtures. Copyright © 2012 John Wiley & Sons, Ltd.     

Multiframe blind image deconvolution with split Bregman method

In the paper, a multiframe blind image deconvolution method based on total variation and framelet regularizer is proposed. An adapted version of the split Bregman method is proposed to efficiently solve the resulting minimization problems. In each iteration, four sub-problems need to be solved, one of which can be very efficiently and easily solved via fast Fourier transform implementation or closed form solution. Both simulated noisy and blurred frames and real degraded frames are used to verify the effectiveness of the proposed method. Comparative experimental results show that the proposed method can efficiently remove the blur and noises and restore high quality sharp image.     

Motion blur parameters estimation for image restoration

This paper deals with estimation of parameters for motion blurred images. The objectives are to estimate the length (L) and the blur angle (θ) of the given degraded image as accurately as possible so that the restoration performance can be optimised. Gabor filter is utilized to estimate the blur angle whereas a trained radial basis function neural network (RBFNN) estimates the blur length. Once these parameters are estimated the conventional restoration is performed. To validate the proposed scheme, simulation has been carried out on standard images as well as in real images subjected to different blur angles and lengths. The robustness of the scheme is also validated in noise situations of different strengths. In all situations, the results have been compared with standard schemes. It is in general observed that the proposed scheme outperforms its counterparts in terms of restoration parameters and visual quality.     

An improved method of unfolding neutron TOF spectrum for low ion temperature inertial confinement fusion

The fuel ion temperature in inertial confinement fusion can be determined from the neutron energy spectrum. For the implosion experiment with low neutron yield, and thus low signal-to-noise ratio, a new technique to unfold the neutron energy spectrum from the observed neutron time-of-flight signal is presented in this paper. This method uses a low-pass filter to remove noise from the signal with a threshold value determined by power spectrum analysis. This technique has been applied to the analysis of the observed neutron time-of-flight signals in the indirect drive implosion experiment conducted on Shenguang III prototype laser facility, and fuel ion temperatures of about 1.0 keV are obtained.     

基于模糊度量的激光水下图像复原的盲去卷积方法

由于水体对激光存在着不可克服的吸收和散射效应,距离选通水下激光成像系统所获得的图像存在不同程度的劣化问题,具有信噪比低、边缘模糊等特点.为提高图像质量,将基于模糊度量的盲去卷积方法应用于激光水下成像的图像复原中.结合威尔斯小角度近似得出的点扩展函数与调制传递函数,分别讨论了最大期望,最小均方与多次乘法迭代盲去卷积算法,...     

Isotope pattern deconvolution-tandem mass spectrometry for the determination and confirmation of diclofenac in wastewaters

Isotope dilution mass spectrometry (IDMS) based on isotope pattern deconvolution (IPD) has been applied here to MS/MS (QqQ) in order to carry out the quantification and confirmation of organic compounds in complex matrix water samples without the use of a methodological IDMS calibration graph. In this alternative approach, the isotope composition of the spiked sample is measured after fragmentation by SRM and deconvoluted into its constituting components (molar fractions of natural abundance and labeled compound) by multiple linear regression (IPD). The procedure has been evaluated for the determination of the pharmaceutical diclofenac in effluent and influent urban wastewaters and fortified surface waters by UHPLC (ESI) MS/MS using diclofenac-d₄ as labeled compound. Calculations were performed acquiring a part and the whole fragment cluster ion, achieving in all cases recoveries within 90–110% and coefficients of variation below 5% for all water samples tested. In addition, potential false negatives arising from the presence of diclofenac-d₂ impurities in the labeled compound were avoided when the proposed approach was used instead of the most usual IDMS calibration procedure. The number of SRM transitions measured was minimized to three to make possible the application of this alternative technique in routine multi-residue analysis.     

A family of new, high order NS-α models arising from helicity correction in Leray turbulence models

This report gives a reinterpretation of the NS-α model which leads to a family of high order NS-α-deconvolution models with NS-α as the zeroth order case. First, we show that the Navier-Stokes-α model arises by adding helicity correction to Leray-α model. Higher order Leray models have recently been proposed in [W. Layton, R. Lewandowski, A high accuracy Leray-deconvolution model of turbulence and its limiting behavior, Anal. Appl. 6 (1) (2008); W. Layton, C. Manica, M. Neda, L. Rebholz, Numerical analysis and computational testing of a high-accuracy Leray-deconvolution model of turbulence, Numer. Methods Partial Differential Equations, in press]: the so-called Leray-deconvolution models, that employ van Cittert approximate deconvolution to decrease consistency error. We use an analogous helicity correction idea to develop a family of higher order accurate NS-α type models, the NS-α-deconvolution models. We prove several mathematical and physical properties for this new family of models and discuss the design of efficient algorithms for them.