基于DSP的LTE TDD上行解传输预编码实现

在时分长期演进(time division-long term evolution,TD-LTE)系统中,为了保证上行传输单载波特性,采用集中式DFT-扩展-OFDM(discrete Fourier transform-spread OFDM)机制.对各种离散傅里叶逆变换(inverse discreteFourie...     

一种块匹配的图像修复算法

在研究Criminisi算法的基础上,提出了一种新的图像修复算法。根据图像待修复点梯度的大小,在源区域中确定其匹配区域的范围,减少搜索次数;以到待修复点距离从小到大的方式搜索匹配块,应用最近最优匹配块对图像进行修复;提出新的置信度更新方法,使更新后的置信度与累积误差成反比。实验表明,本文提出的图像修复算法具有较好的图象修复效果,并且计算复杂度低,效率高。     

同科电子各多重态的微观态个数计算公式

本文根据文献给出的一种推求同科电子组态的原子谱项的方法,利用"矢量和的定则"推导出了同科电子各多重态的微观态个数计算公式,并具体计算了nf2、nf5组态的各多重态的微观态个数,结果与根据文献给出的谱项计算各多重态的微观态个数完全一致.     

The Effect of Estimating Parameters on Long‐Term Forecasts for Cointegrated Systems

This paper concerns Long‐term forecasts for cointegrated processes. First, it considers the case where the parameters of the model are known. The paper analytically shows that neither cointegration nor integration constraint matters in Long‐term forecasts. It is an alternative implication of Long‐term forecasts for cointegrated processes, extending the results of previous influential studies. The appropriate Mote Carlo experiment supports our analytical result. Secondly, and more importantly, it considers the case where the parameters of the model are estimated. The paper shows that accuracy of the estimation of the drift term is crucial in Long‐term forecasts. Namely, the relative accuracy of various Long‐term forecasts depends upon the relative magnitude of variances of estimators of the drift term. It further experimentally shows that in finite samples the univariate ARIMA forecast, whose drift term is estimated by the simple time average of differenced data, is better than the cointegrated system forecast, whose parameters are estimated by the well‐known Johansen's ML method. Based upon finite sample experiments, it recommends the univariate ARIMA forecast rather than the conventional cointegrated system forecast in finite samples for its practical usefulness and robustness against model misspecifications. Copyright © 2011 John Wiley & Sons, Ltd.     

The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH‐MIDAS Approach

This paper applies the GARCH‐MIDAS (mixed data sampling) model to examine whether information contained in macroeconomic variables can help to predict short‐term and long‐term components of the return variance. A principal component analysis is used to incorporate the information contained in different variables. Our results show that including low‐frequency macroeconomic information in the GARCH‐MIDAS model improves the prediction ability of the model, particularly for the long‐term variance component. Moreover, the GARCH‐MIDAS model augmented with the first principal component outperforms all other specifications, indicating that the constructed principal component can be considered as a good proxy of the business cycle. Copyright © 2013 John Wiley & Sons, Ltd.     

高阶具非线性中立项时滞微分方程正解的存在性

利用控制收敛定理和压缩映射原理研究了一类具非线性中立项时滞微分方程有界正解的存在性,获得了其存在有界正解的充分条件．     

广义Laplace-Stieltjes变换所表示整函数的β级和广义型

该文研究了由广义Laplace-Stieltjes变换所表示的整函数的增长性.首先介绍了由广义Laplace-Stieltjes变换所表示的整函数在圆周上的最大模、最大项的定义;其次研究并得到了由最大模、最大项所表示的整函数的β级、广义型和用A_n、λ_n所表示的整函数的β级、广义型之间的等价关系;最后给出了定理的相应推论,得到了Laplace-Stieltjes变换所表示的整函数在圆周上的β级、广义型.     

科技术语自动提取技术——现状与思考

文章简要介绍了自动术语提取任务的定义、主要方法和评价指标。针对传统的自动术语提取方法,以互信息、t值、tf-idf、C/NC-value为例介绍了单元度和术语度的概念;针对自动术语标注方法,主要介绍了基于序列标注的建模思想。从提取效果来看,现有自动术语提取技术距离期望仍有差距,文章也尝试给出了一些值得探索的方向。     

对IWRM中文译法的若干探讨

国际社会近年普遍推行的IWRM已成为重要的英文术语,但其中文翻译多为“水资源综合管理”及其他一些形似而神异的表述,均与英文本意存在一定的差异。本文就IWRM中文译法给人们带来的困扰进行了溯源研究,分析目前译法存在的问题,对国际机构几种英语定义进行了探讨,最后提出与IWRM原意相符的中文译法。     

New evidence on the robust identification of news shocks: Role of revisions in utilization‐adjusted TFP series and term structure data

Data revisions and selections of appropriate forwarding‐looking variables have a major impact on true identification of news shocks and quality of research findings derived from structural vector autoregression (SVAR) estimation. This paper revisits news shocks to identify the role of different vintages of total factor productivity (TFP) series and term structure of interest rates as major prognosticators of future economic growth. There is a growing strand of literature regarding the use of utilization‐adjusted TFP series, provided by Fernald (Federal Reserve Bank of San Francisco, Working Paper Series, 2014) for identification of news shocks. We reestimate Barsky and Sims' (Journal of Monetary Economics, 2011, 58, 273–289) empirical analysis by employing 2007 and 2015 vintages of TFP data. We find substantial quantitative as well as qualitative differences among impulse response functions when using 2007 and 2015 vintages of TFP data. Output and hours initially decline, followed by quick reversal of both variables. In sharp contrast to results achieved by the 2007 vintage of TFP data, results achieved by the 2015 vintage of TFP data depict that output and hours will increase in response to positive TFP shock. By including term structure data in our VAR specification, total surprise technology shock and news shock account for 97% and 92% of the forecast error variance in total TFP and total output respectively. We find that revisions in TFP series over time ultimately impact the conclusion regarding news shocks on business cycles. Our results support the notion that term structure data help in better identification of news shock as compared to other forward‐looking variables.