Extended Gauss–Markov Theorem for Nonparametric Mixed-Effects Models

The Gauss–Markov theorem provides a golden standard for constructing the best linear unbiased estimation for linear models. The main purpose of this article is to extend the Gauss–Markov theorem to include nonparametric mixed-effects models. The extended Gauss–Markov estimation (or prediction) is shown to be equivalent to a regularization method and its minimaxity is addressed. The resulting Gauss–Markov estimation serves as an oracle to guide the exploration for effective nonlinear estimators adaptively. Various examples are discussed. Particularly, the wavelet nonparametric regression example and its connection with a Sobolev regularization is presented.     

Numerical analysis and computational testing of a high accuracy Leray‐deconvolution model of turbulence

We study a computationally attractive algorithm (based on an extrapolated Crank‐Nicolson method) for a recently proposed family of high accuracy turbulence models, the Leray‐deconvolution family. First we prove convergence of the algorithm to the solution of the Navier‐Stokes equations and delineate its (optimal) accuracy. Numerical experiments are presented which confirm the convergence theory. Our 3d experiments also give a careful comparison of various related approaches. They show the combination of the Leray‐deconvolution regularization with the extrapolated Crank‐Nicolson method can be more accurate at higher Reynolds number that the classical extrapolated trapezoidal method of Baker (Report, Harvard University, 1976). We also show the higher order Leray‐deconvolution models (e.g. N = 1,2,3) have greater accuracy than the N = 0 case of the Leray‐α model. Numerical experiments for the 2d step problem are also successfully investigated. Around the critical Reynolds number, the low order models inhibit vortex shedding behind the step. The higher order models, correctly, do not. To estimate the complexity of using Leray‐deconvolution models for turbulent flow simulations we estimate the models' microscale.© 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2008     

A note on wavelet density deconvolution for weakly dependent data

In this paper we investigate the performance of a linear wavelet-type deconvolution estimator for weakly dependent data. We show that the rates of convergence which are optimal in the case of i.i.d. data are also (almost) attained for strongly mixing observations, provided the mixing coefficients decay fast enough. The results are applied to a discretely observed continuous-time stochastic volatility model.     

A study of the practical limitations of principal components analysis and the labelling of unresolved HPLC peaks

Summary The method of iterative target transformation factor analysis (ITTFA) used in conjunction with second derivative peak finding has shown to be a practical method for the peak deconvolution and reconstruction of HPLC chromatograms and spectra. The second derivative method of peak finding is acceptable for resolutions above 0.5 for peaks of similar heights. Above 0.5 resolution the labelling gives correct results where the spectra are substantially different and also when reasonably similar. Below this value the peak labelling was still accurate where the spectra were different. Solvent effects on the spectra of the compounds studied are small and do not hinder the peak labelling process. Thus small “local” libraries are feasible. Presented at the 17th International Symposium on Chromatography, September 25–30, 1988. Vienna, Austria.     

Monitoring and classification of wastewater quality using supervised pattern recognition techniques and deterministic resolution of molecular absorption spectra based on multiwavelength UV spectra deconvolution

A field flow approach for the in situ monitoring of wastewater quality is developed and assessed in this work, based on a combination of methods employing deconvolution of molecular absorption spectra and in situ/on-line analysis of wastewater effluent of various origin. The approach involves in situ immersion probes to monitor basic physicochemical parameters followed by UV spectrum deconvolution in order to provide a rapid estimate of organic matter, suspended solids and nitrate and on-line analysis of phosphates in a fully automated setup. The collected data are then treated with a series of supervised pattern recognition techniques in order to classify wastewater effluent according to their origin in three major categories namely municipal, industrial and hospital. The results suggest that the method affords a good approximation of realistic concentrations, as determined by reference methods, while it affords a good classification among various wastewater effluents of different origin. In that manner, the method enables a rapid inference of treated wastewater quality and a robust assessment of treatment process state, especially with regards to violations of effluent quality parameters.     

A piecewise local regularized Richardson-Lucy algorithm for remote sensing image deconvolution

As it is not possible to obtain an accurate point spread function (PSF) in remote sensing imaging, classic deconvolution methods such as Wiener filtering often introduce strong noise and ringing artifacts, which contaminate the restored images. In this paper, we modify the standard Richarson-Lucy (RL) algorithm with a piecewise local regularization term and combine it with residual deconvolution method. Experimental results show that it is effective in suppressing negative effects, and images with rich details and sharp edges are obtained.     

瞬时混合盲源分离和最优波束形成的关系研究

最优波束形成和盲源分离是近几十年迅速发展起来的两种重要阵列信号处理方法,在瞬时混合情况下它们具有相似的信号模型,所以本文研究了二者之间的关系。指出,当不存在噪声时,多数盲源分离算法构造的是最优波束形成;当存在噪声时,可以利用盲源分离算法估计的信号导向向量设计最优波束形成。计算机仿真实验验证了这一结论。     

基于盲解卷积的水声信号恢复技术

信号在环境复杂多途严重的水声波导中传输后,接收到的信号时间长度被拉长,信号是失真的。在许多实际应用中,常常希望从已失真的接收信号中把原始信号波形恢复出来。本文利用盲解卷积技术对水声信号恢复进行研究。理论推演表明,在垂直阵条件下用人造的格林函数可成功地代替水声信道真实的格林函数,可以把非线性关系化解为线性关系,从而推导出依靠基阵记录下的信息去确定声源宽带信号原始波形和环境传播特征的公式和步骤。声场数值计算对6种海底类型进行,恢复后的宽带信号与原始信号的归一化相关系数均大于0.945,对硬海底多途严重的情况,收效特别明显,证明该方法的有效性。在青岛海试中恢复后信号的相关系数平均值为0.933,在青岛海试中利用这种解卷积技术去恢复信号是成功的。     

Best Fourier Approximation and Application in Efficient Blurred Signal Reconstruction

We expand upon the known results on sharp linear Fourier methods of approximation where the approximation is the best in terms of both rate and constant among all polynomial procedures of approximation. So far these results have been studied due to their mathematical beauty rather than their practical importance. In this paper we show that they are the core mathematics underlying best statistical methods of solving noisy ill-posed problems. In particular, we suggest a procedure for recovery of noisy blurred signals based on samples of small sizes where a traditional statistics concludes that the complexity of such a setting makes the problem not worthy of a further study. Thus, we present a problem where a combination of the classical approximation theory and statistics leads to interesting practical results.     

Energy transfer kinetics of phycoerythrocyanins (PECs) from the cyanobacterium Anabaena variabilis(Ⅰ)

The excitation energy transfer processes in nionomeric phycoerythrocyanins ( PEC)have been studied in detail using steady-state and time-resolved fluorescence spectra techniques as well as the deconvolution fech nique of spectra.The results indicate that the energy transfer processes should take place between α84 PVB md β8 or β155-PCB chromophores,the time constants of energy transfer are 34.7 and 130 ps individually;the component with lifetime of 1.57 ns originates from the fluorescence lifetime of the terminal emitter of β84 and /or β155 PCB chre-mophores; and the component with lifetime of 515 ps might be assigned to the energy transfer between two PCB chro mophores of β subunit.