GENERAL DECAY FOR A VISCOELASTIC EQUATION OF VARIABLE COEFFICIENTS WITH A TIME-VARYING DELAY IN THE BOUNDARY FEEDBACK AND ACOUSTIC BOUNDARY CONDITIONS

A variable coefficient viscoelastic equation with a time-varying delay in the boundary feedback and acoustic boundary conditions and nonlinear source term is considered.Under suitable assumptions, general decay results of the energy are established via suitable Lyapunov functionals and some properties of the convex functions. Our result is obtained without imposing any restrictive growth assumption on the damping term and the elements of the matrix A and the kernel function g.

Refinement of Fourier Coefficients from the Stokes Deconvoluted Profile

Computer-aided experimental technique was used to study the Stokes deconvolution of X-ray diffraction profile. Considerable difference can be found between the Fourier coefficients obtained from the deconvolutions of singlet and doublet experimental profiles. Nevertheless, the resultant physical profiles corresponding to singlet and doublet profiles are identical. An approach is proposed to refine the Fourier coefficients, and the refined Fourier coefficients coincide well with that obtained from the deconvolution of singlet experimental profile.

ON THE FOURIER-VILENKIN COEFFICIENTS

In this article, we prove the following statement that is true for both unbounded and bounded Vilenkin systems： for any ε∈ （0, 1）, there exists a measurable set E C [0, 1） of measure bigger than 1 - s such that for any function f ∈ LI[0, 1）, it is possible to find a function g ∈ L^1 [0, 1） coinciding with f on E and the absolute values of non zero Fourier coefficients of g with respect to the Vilenkin system are monotonically decreasing.

STUDY ON FREQUENCY ESTIMATION BASED ON WEIGHTED LEAST SQUARE METHOD WITH THREE FOURIER COEFFICIENTS

In this paper,a sinusoidal signal frequency estimation algorithm is proposed by weighted least square method.Based on the idea of Provencher,three biggest Fourier coefficients in the maximum periodogram are considered,the Fourier coefficients can be written as three equations about the amplitude,phase,and frequency,and the frequency is estimated by solving equations.Because of the error of measurement,weighted least square method is used to solve the frequency equation and get the signal frequency.It is shown that the proposed estimator can approach the Cramer-Rao Bound(CRB)with a low Signal-to-Noise Ratio(SNR)threshold and has a higher accuracy.

ADDITIVE HAZARDS MODEL WITH TIME-VARYING REGRESSION COEFFICIENTS

This article discusses regression analysis of failure time under the additive hazards model, when the regression coefficients are time-varying. The regression coefficients are estimated locally based on the pseudo-score function [12] in a window around each time point. The proposed method can be easily implemented, and the resulting estimators are shown to be consistent and asymptotically normal with easily estimated variances. The simulation studies show that our estimation procedure is reliable and useful.

Quadrature formulas for Fourier-Chebyshev coefficients

The aim of this work is to construct a new quadrature formula for Fourier Chebyshev coef ficients based on the divided differences of the integrand at points 1, 1 and the zeros of the n th Chebyshev polynomial of the second kind. The interesting thing is that this quadrature rule is closely related to the well known Gauss Turn quadrature formula and similar to a recent result of Micchelli and Sharma, extending a particular case due to Micchelli and Rivlin.

A Simulation Study on Comparing General Class of Semiparametric Transformation Models for Survival Outcome with Time-Varying Coefficients and Covariates

The consideration of the time-varying covariate and time-varying coefficient effect in survival models are plausible and robust techniques. Such kind of analysis can be carried out with a general class of semiparametric transformation models. The aim of this article is to develop modified estimating equations under semiparametric transformation models of survival time with time-varying coefficient effect and time-varying continuous covariates. For this, it is important to organize the data in a counting process style and transform the time with standard transformation classes which shall be applied in this article. In the situation when the effect of coefficient and covariates change over time, the widely used maximum likelihood estimation method becomes more complex and burdensome in estimating consistent estimates. To overcome this problem, alternatively, the modified estimating equations were applied to estimate the unknown parameters and unspecified monotone transformation functions. The estimating equations were modified to incorporate the time-varying effect in both coefficient and covariates. The performance of the proposed methods is tested through a simulation study. To sum up the study, the effect of possibly time-varying covariates and time-varying coefficients was evaluated in some special cases of semiparametric transformation models. Finally, the results have shown that the role of the time-varying covariate in the semiparametric transformation models was plausible and credible.

Facial Expression Recognition Based on Local Fourier Coefficients and Facial Fourier Descriptors

The recent boom of mass media communication (such as social media and mobiles) has boosted more applications of automatic facial expression recognition (FER). Thus, human facial expressions have to be encoded and recognized through digital devices. However, this process has to be done under recurrent problems of image illumination changes and partial occlusions. Therefore, in this paper, we propose a fully automated FER system based on Local Fourier Coefficients and Facial Fourier Descriptors. The combined power of appearance and geometric features is used for describing the specific facial regions of eyes-eyebrows, nose and mouth. All based on the attributes of the Fourier Transform and Support Vector Machines. Hence, our proposal overcomes FER problems such as illumination changes, partial occlusion, image rotation, redundancy and dimensionality reduction. Several tests were performed in order to demonstrate the efficiency of our proposal, which were evaluated using three standard databases: CK+, MUG and TFEID. In addition, evaluation results showed that the average recognition rate of each database reaches higher performance than most of the state-of-the-art techniques surveyed in this paper.

Order of Magnitude of Multiple Fourier Coefficients

The order of magnitude of multiple Fourier coefficients of complex valued functions of generalized bounded variations like （∧^1,.. .,∧^N）BV^（p） and r-BV, over [0,2π]^ N, are estimated.

A High-Order Conservative Numerical Method for Gross-Pitaevskii Equation with Time-Varying Coefficients in Modeling BEC

We propose a high-order conservative method for the nonlinear Sehodinger/Gross-Pitaevskii equation with time- varying coefficients in modeling Bose Einstein condensation （BEC）. This scheme combined with the sixth-order compact finite difference method and the fourth-order average vector field method, finely describes the condensate wave function and physical characteristics in some small potential wells. Numerical experiments are presented to demonstrate that our numerical scheme is efficient by the comparison with the Fourier pseudo-spectral method. Moreover, it preserves several conservation laws well and even exactly under some specific conditions.

Azimuthal elastic impedance-based Fourier coefficient variation with angle inversion for fracture weakness

Quantitative inversion of fracture weakness plays an important role in fracture prediction.Considering reservoirs with a set of vertical fractures as horizontal transversely isotropic media,the logarithmic normalized azimuthal elastic impedance(EI)is rewritten in terms of Fourier coefficients(FCs),the 90°ambiguity in the azimuth estimation of the symmetry axis is resolved by judging the sign of the second FC,and we choose the FCs with the highest sensitivity to fracture weakness and present a feasible inversion workflow for fracture weakness,which involves:(1)the inversion for azimuthal EI datasets from observed azimuthal angle gathers;(2)the prediction for the second FCs and azimuth of the symmetry axis from the estimated azimuthal EI datasets;and(3)the estimation of fracture weakness combining the extracted second FCs and azimuth of the symmetry axis iteratively,which is constrained utilizing the Cauchy sparse regularization and the low-frequency regularization in a Bayesian framework.Tests on synthetic and field data demonstrate that the 90°ambiguity in the azimuth estimation of the symmetry axis has been removed,and reliable fracture weakness can be obtained when the estimated azimuth of the symmetry axis deviates less than 30°,which can guide the prediction of fractured reservoirs.

P-FFT and FG-FFT with real coefficients algorithm for the EFIE

In order to reduce the storage amount for the sparse coefficient matrix in pre-corrected fast Fourier transform （P-FFT） or fitting the Green function fast Fourier transform （FG-FFT）, the real coefficients are solved by improving the solution method of the coefficient equations. The novel method in both P-FFT and FG-FFT for the electric field integral equation （EFIE） is employed. With the proposed method, the storage amount for the sparse coefficient matrix can be reduced to the same level as that in the adaptive integral method （AIM） or the integral equation fast Fourier transform （IE-FFT）. Meanwhile, the new algorithms do not increase the number of the FFTs used in a matrix-vector product, and maintain almost the same level of accuracy as the original versions. Besides, in respect of the time cost in each iteration, the new algorithms have also the same level as AIM （or IE- FFF）. The numerical examples demonstrate the advantages of the proposed method.

Numerical Analysis of Upwind Difference Schemes for Two-Dimensional First-Order Hyperbolic Equations with Variable Coefficients

In this paper, we consider the initial-boundary value problem of two-dimensional first-order linear hyperbolic equation with variable coefficients. By using the upwind difference method to discretize the spatial derivative term and the forward and backward Euler method to discretize the time derivative term, the explicit and implicit upwind difference schemes are obtained respectively. It is proved that the explicit upwind scheme is conditionally stable and the implicit upwind scheme is unconditionally stable. Then the convergence of the schemes is derived. Numerical examples verify the results of theoretical analysis.

Recurrent formula of Bernoulli numbers and the relationships among the coefficients of beam,Bernoulli numbers and Euler numbers

Based on the differential equation of the deflection curve for the beam,the equation of the deflection curve for the simple beamis obtained by integral. The equation of the deflection curve for the simple beamcarrying the linear load is generalized,and then it is expanded into the corresponding Fourier series.With the obtained summation results of the infinite series,it is found that they are related to Bernoulli num-bers and π. The recurrent formula of Bernoulli numbers is presented. The relationships among the coefficients of the beam,Bernoulli numbers and Euler numbers are found,and the relative mathematical formulas are presented.

Partial Time-Varying Coefficient Regression and Autoregressive Mixed Model

Regression and autoregressive mixed models are classical models used to analyze the relationship between time series response variable and other covariates. The coefficients in traditional regression and autoregressive mixed models are constants. However, for complicated data, the coefficients of covariates may change with time. In this article, we propose a kind of partial time-varying coefficient regression and autoregressive mixed model and obtain the local weighted least-square estimators of coefficient functions by the local polynomial technique. The asymptotic normality properties of estimators are derived under regularity conditions, and simulation studies are conducted to empirically examine the finite-sample performances of the proposed estimators. Finally, we use real data about Lake Shasta inflow to illustrate the application of the proposed model.

Partial Time-Varying Coefficient Regression and Autoregressive Mixed Model

Regression and autoregressive mixed models are classical models used to analyze the relationship between time series response variable and other covariates. The coefficients in traditional regression and autoregressive mixed models are constants. However, for complicated data, the coefficients of covariates may change with time. In this article, we propose a kind of partial time-varying coefficient regression and autoregressive mixed model and obtain the local weighted least-square estimators of coefficient functions by the local polynomial technique. The asymptotic normality properties of estimators are derived under regularity conditions, and simulation studies are conducted to empirically examine the finite-sample performances of the proposed estimators. Finally, we use real data about Lake Shasta inflow to illustrate the application of the proposed model.

对称幂平方L-函数Fourier系数的高次均值估计

设f(z)为全模群SL(2,Z)上权为偶数k的Hecke特征形式,L(s,sym^(2)f)为其对应的对称幂平方L-函数,λsym^(2)f(n)为对称幂平方L-函数L(s,sym^(2)f)的Fourier展开式中第n个正规化Fourier系数.本文借助Newton和Thorne近期关于函数Symjf的重要工作以及自守L-函数的亚凸界和均值估计结果,研究了λsym^(2)f(n)在四个整数平方和序列上的三次均值估计和四次均值估计,得到了均值估计的渐近公式,改进了之前的结果.

一种基于DCT系数和Fourier描述子的人脸识别方法

研究了一种基于人脸细节信息和外形轮廓信息相结合的人脸识别方法.用DCT(离散余弦变换)系数集表示人脸细节信息,傅立叶描述子集表示人脸轮廓信息,用基于相似性的匹配方式将待测人脸的两种信息分别与数据库中的人脸进行匹配,并根据光照条件将两个匹配结果进行合理的融合作为最终的匹配结果.由于人脸外形比较稳定,并且傅立叶描述子对旋转不敏感,最重要的是,在匹配过程中创造性地利用了实时光照信息进行融合,因此,这种方法不仅稳定,还可以较好地弥补传统二维人脸识别系统极易受到光照、姿态等因素影响的这个缺点.

对离散Fourier变换公式四种形式的讨论

分析了离散Fourier变换公式中求和符号前的常系数选取规律,提出了离散Fourier变换公式的分类概念,将离散Fourier变换公式分为通用型、缩频扩谱型、缩谱扩频型和频谱均衡型等4种类型;讨论了4种不同类型的离散Fourier变换公式的内在联系和一致性,分析了各种形式的离散Fourier变换公式所强调的侧重面,并讨论了它们的适用范围.主要结论为:离散Fourier正、逆变换公式中求和符号前常系数之乘积等于信号采样数的倒数;按此规律调整常系数,可以有重点地对信号开展频-谱分析;缩频扩谱型、缩谱扩频型离散Fourier变换公式分别适合于弱幅信号、低频信号的处理.

基于Fourier-Mellin变换和相干系数法的重复轨道干涉SAR图像配准新方法

相对于单轨双天线InSAR系统,重复轨道InSAR系统由于轨道不能完全平行,导致InSAR图像对间存在夹角,使其配准更为困难。该文针对非平行重复轨道的InSAR问题,提出了一种结合Fourier-Mellin变换和相干系数法的InSAR图像配准算法,对存在夹角的SAR复图像对进行精确配准。该方法用于粗配准时,通过引入非线性图像幅度变换预处理,克服了Fourier-Mellin变换无法直接处理SAR图像对幅度分布动态范围大且不均匀的问题,而用于精配准时,通过引入相干系数法,精确估计了复图像对之间存在的微小角度。以SIR-C/X重复轨道的X波段SAR数据为例,详细比较了传统相干系数配准算法和该文算法在配准精度和计算时间上的差异,从而验证了算法的有效性。