数字线性计数率计

计数率计能够直接监视、测量和指示输入脉冲的平均计数率。介绍了数字线性计数率计的E-PLD设计。它比模拟线性计数率计有更高的精度、更好的线性和稳定性。

Linear numerical calculation method for obtaining critical point,pore fluid,and framework parameters of gas-bearing media

Up to now, the primary method for studying critical porosity and porous media are experimental measurements and data analysis. There are few references on how to numerically calculate porosity at the critical point, pore fluid-related parameters, or framework-related parameters. So in this article, we provide a method for calculating these elastic parameters and use this method to analyze gas-bearing samples. We first derive three linear equations for numerical calculations. They are the equation of density p versus porosity Ф, density times the square of compressional wave velocity p Vp^2 versus porosity, and density times the square of shear wave velocity pVs^2 versus porosity. Here porosity is viewed as an independent variable and the other parameters are dependent variables. We elaborate on the calculation steps and provide some notes. Then we use our method to analyze gas-bearing sandstone samples. In the calculations, density and P- and S-velocities are input data and we calculate eleven relative parameters for porous fluid, framework, and critical point. In the end, by comparing our results with experiment measurements, we prove the viability of the method.

Robustifying Biased Estimation in Linear Model

The parameter estimation problem in linear model is considered when multicollinearity and outliers exist simultaneously.A class of new estimators,robust general shrunken estimators,are proposed by grafting the robust estimation techniques philosophy into the biased estimator,and their statistical properties are discussed.By appropriate choices of the shrinking parameter matrix,we obtain many useful and important estimators.A numerical example is used to illustrate that these new estimators can not only effectively overcome difficulty caused by multicollinearity but also resist the influence of outliers.

能量色散X射线荧光光谱仪校准方法的探讨

本文探讨了能量色散X射线荧光光谱仪的校准方法,包括部件计量性能的校准如能量分辨力、重复性、稳定性、峰背比、计数线性等,同时也对利用标准物质进行整机校准的方法如示值误差和重复性的进行了说明,给出了相关的计量性能要求,为实验室和计量机构评价仪器提供了参考。

Modular Transformation Formula for Certain Series

In this paper we correct a transformation formula given by T.M.Apostol in reference [1]. Using this formula, we get an estimation of ζ(3).

Computer Algebra and Solutions to the Karamoto-Sivashinsky Equation

The method of Riccati equation is extended for constructing travelling wave solutions of nonlinear partial differential equations. It is applied to solve the Karamoto-Sivashinsky equation and then its more new explicit solutions have been obtained. From the results given in this paper, one can see the computer algebra plays an important role in this procedure.

Linear Support Vector Machine Based Inter-harmonic Modeling and Parameter Estimation

There are often system. The high measure many inter-harmonics in power t accuracy of inter-harmonics order, amplitude and initial phase is needed. A new approach is presented for inter-harmonic modeling and parameter estimation based on linear support vector machine （SVM）. Firstly, parameter estimation of linear model is realized based on standard linear SVM. Then, interharmonic model is transformed to a linear model according to trigonometric functions. The approach obtains order of inter-harmonic model with windowed Blackman-Tukey （BT） spectrum analysis, and gets number and frequency of harmonics. Finally, the linear SVM is applied to estimate the inter-harmonic parameters, amplitude and initial phase. The simulation results show that the proposed approach has high precision and good antinoise. The accuracy of three parameters are all higher than 98%.

Applications of Computer Algebra in Solving Nonlinear Evolution Equations

With the use of computer algebra, the method that straightforwardly leads to travelling wave solutions is presented. The compound KdV-Burgers equation and KP-B equation are chosen to illustrate this approach. As a result, their abundant new soliton-like solutions and period form solutions are found.

LMMSE-based SAGE channel estimation and data detection joint algorithm for MIMO-OFDM system

A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE）- based space-alternating generalized expectation-maximization （SAGE） algorithm. In the proposed algorithm, every sub-frame of the MIMO-OFDM system is divided into some OFDM sub-blocks and the LMMSE-based SAGE algorithm in each sub-block is used. At the head of each sub-flame, we insert training symbols which are used in the initial estimation at the beginning. Channel estimation of the previous sub-block is applied to the initial estimation in the current sub-block by the maximum-likelihood （ML） detection to update channel estimatjon and data detection by iteration until converge. Then all the sub-blocks can be finished in turn. Simulation results show that the proposed algorithm can improve the bit error rate （BER） performance.

Diagnostics in generalized nonlinear models based on maximum L_q-likelihood estimation

In order to detect whether the data conforms to the given model, it is necessary to diagnose the data in the statistical way. The diagnostic problem in generalized nonlinear models based on the maximum Lq-likelihood estimation is considered. Three diagnostic statistics are used to detect whether the outliers exist in the data set. Simulation results show that when the sample size is small, the values of diagnostic statistics based on the maximum Lq-likelihood estimation are greater than the values based on the maximum likelihood estimation. As the sample size increases, the difference between the values of the diagnostic statistics based on two estimation methods diminishes gradually. It means that the outliers can be distinguished easier through the maximum Lq-likelihood method than those through the maximum likelihood estimation method.

Positive solutions of singular superlinear fourth order boundary value problem

The cone theorem and the fixed point index are used to investigate the positive solution of singular superlinear boundary value problem for a fourth order nonlinear differential equation.

Some Notes for Toeplitz Matrix

In this paper,we study real symmetric Toeplitz matrices commutable with tridiagonal matrices, present more detailed results than those in [1], and extend them to nonsymmetric Toeplitz matrices. Also, complex Toeplitz matrices, especially the corresponding matrices of lower order, are discussed.

Finite Element Analysis and Linear Regression of Maximum Temperature for Inner Wall of Chimney Foundation

The uniform design method was adopted and the twenty-four groups of different geometric and physical pa-rameters were chosen. The finite element model was built. Comparisons between the simulation results and the test re-sults prove that the simulation results are correct. The distribution of the temperature field of the chimney foundationwas analyzed. The multivariate linear regression of the hightest tomperature was performed on the inner wall of thechimney foundation by the numerical calculated results. The fitting property of the highest temperature with six influ-ence factors was obtained. A simple method for the calculation of the temperature field of the chimney foundation wasprovided.

Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data

This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution.

Retrieval algorithm of sea surface wind vectors for WindSat based on a simple forward model

WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center （NDBC）, root mean square errors are 1.2 rn/s and 30~ for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.

Design parameter optimization of beam foundation on soft soil layer with nonlinear finite element

Finite element method was performed to investigate the influences of beam stiffness, foundation width and cushion thickness on the beating capacity of beam foundation on underlying weak laminated clay. The comparison between numerical results and results from field test including plate-bearing test and foundation settlement observation shows reasonable agreement. According to the numerical results, the beam width, length, cross section and cushion thickness were optimized. The results show that the stresses in subgrade soil decrease greatly with increasing the cushion thickness and width of foundation. However, the foundation settlement and influencing depth of displacement also increase correspondingly under conditions of relatively thinner cushion thickness. For the foundations on underlying weak layer, increasing foundation width merely might be inadequate for improving the bearing capacity, and the appropriate width and cushion thickness depend on the response of subgrade. A comparison between rigid and flexible beams was also discussed. The influence of a flexible beam foundation on subgrade is relatively smaller under the same loading conditions, and the flexible beam foundation appears more adaptable to various subgrades. The proposed flexible beam foundation was adopted in engineering. According to the calculation results, beam width of 2.4 m and cushion thickness of 0.8 m are proposed, and a flexible beam foundation is applied in the optimized design, which is confirmed reasonable by the actual engineering.

Computation of the Simplest Normal Forms for Resonant Double Hopf Bifurcations System Based on Lie Transform

The simplest normal form of resonant double Hopf bifurcation was studied based on Lie operator. The coefficients of the simplest normal forms of resonant double Hopf bifurcation and the nonlinear transformations in terms of the original system coefficients were given explicitly. The nonlinear transformations were used for reducing the lower- and higher-order normal forms, and the rank of system matrix was used to determine the coefficient of normal form which could be reduced. These make the gained normal form simpler than the traditional one. A general program was compiled with Mathematica. This program can compute the simplest normal form of resonant double Hopf bifurcation and the non-resonant form up to the 7th order.

On the Value Distributions of Walsh Spectrum of Two Classes of Plateaued Functions

Based on the properties of trace functions and quadratic forms, this paper presents value distributions of Walsh spectrum of the Plateaued functions of the form Tr（R（x）） with n=3r or 4r variables, where r 〉 1 is an odd integer. Our results can be used to determine the numbers of non-zero Walsh spectrum values and the nonlinearities of these functions, and estimate their resiliency orders. Especially, the value distributions can be used to deduce the tight lower bounds of the second order nonlinearity of two classes of Boolean functions. It is demonstrated that our bounds are better than the previously obtained bounds.

Gross Error Detection and Identification Based on Parameter Estimation for Dynamic Systems

The detection and identification of gross errors, especially measurement bias, plays a vital role in data reconciliation for nonlinear dynamic systems. Although parameter estimation method has been proved to be a pow-erful tool for bias identification, without a reliable and efficient bias detection strategy, the method is limited in ef-ficiency and cannot be applied widely. In this paper, a new bias detection strategy is constructed to detect the pres-ence of measurement bias and its occurrence time. With the help of this strategy, the number of parameters to be es-timated is greatly reduced, and sequential detections and iterations are also avoided. In addition, the number of de-cision variables of the optimization model is reduced, through which the influence of the parameters estimated is reduced. By incorporating the strategy into the parameter estimation model, a new methodology named IPEBD (Improved Parameter Estimation method with Bias Detection strategy) is constructed. Simulation studies on a con-tinuous stirred tank reactor (CSTR) and the Tennessee Eastman (TE) problem show that IPEBD is efficient for eliminating random errors, measurement biases and outliers contained in dynamic process data.

Polarization Oblique Projection Based Self-Interference Cancellation against PA Nonlinear Distortion in MIMO Full Duplex System

In MIMO full duplex system,power amplifier(PA) nonlinearity limits the self-interference(SI) cancellation seriously. Most existing methods need to model and estimate the PA nonlinearity in order to reconstruct the SI,however the estimation error caused by the mismatch between the estimated PA model and the actual PA property still impacts the cancellation ability,especially when the transmit power is high. In this paper we propose a polarization oblique projection based self-interference cancellation method which does not need to estimate the PA nonlinearity coefficients. It exploits the polarization state information of the signals which is immune to the PA nonlinearity,and establishes an oblique projection operator to cancel the SI. Numerical results and analysis demonstrate that it can cancel the nonlinear SI effectively. Moreover the signal to interfere plus noise ratio(SINR) and the achievable sum rate do not deteriorate when the transmit power is high. Further,the upper bound of the achievable sum rate can be more than twice that of the half duplex.