基于多对非对称直方图修改的可逆信息隐藏

传统基于非对称直方图修改的图像可逆信息隐藏算法存在大量像素无效修改的问题.针对此问题,提出了一种基于多对非对称预测误差直方图修改的可逆信息隐藏方案.该方案结合了非对称直方图修改算法的优势和多直方图修改算法的特点,选择图像的平滑区域进行非对称直方图修改以嵌入信息.在达到发挥非对称直方图补偿还原效应的同时,能进一步减少像素...     

Optimized LDPC differential-encoded 16QAM scheme for high-speed transmission systems

The 16-ary quadrature amplitude modulation （16QAM） is a high spectral efficient scheme for high-speed transmission systems. To remove the phase ambiguity in the coherent detection system, differential-encoded 16QAM （DE-16QAM） is usually used, however, it will cause performance degradation about 3 dB as compared to the conventional 16QAM. To overcome the performance loss, a serial concatenated system with outer low density parity check （LDPC） codes and inner DE-16QAM is proposed. At the receiver, joint iterative differential demodulation and decoding （ID） is carried out to approach the maximum likelihood performance. Moreover, a genetic evolution algorithm based on the extrinsic information transfer chart is proposed to optimize the degree distribution of the outer LDPC codes. Both theoretical analyses and simulation results indicate that this algorithm not only compensates the performance loss, but also obtains a significant performance gain, which is up to 1 dB as compared to the conventional non-DE-16QAM.     

FORECASTING ：EXCHANGE RATES： AN OPTIMAL APPROACH

This paper looks at forecasting daily exchange rates for the United Kingdom, European Union, and China. Here, the authors evaluate the forecasting performance of neural networks （NN）, vector singular spectrum analysis （VSSA）, and recurrent singular spectrum analysis （RSSA） for fore casting exchange rates in these countries. The authors find statistically significant evidence based on the RMSE, that both VSSA and RSSA models outperform NN at forecasting the highly unpredictable exchange rates for China. However, the authors find no evidence to suggest any difference between the forecasting accuracy of the three models for UK and EU exchange rates.     

基于LSTM-HFTS-EC的PM2.5区间多尺度组合预测研究

针对PM2.5传统点值预测会损失浓度值的波动信息,进而无法充分表示和估计其波动和变化的区间范围,提出了一种基于长短期记忆模型(LSTM)-混合模糊时间序列(HFTS)-误差修正(EC)的PM2.5区间多尺度组合预测方法;在结合深度学习和区间多尺度分解方法的基础上,进一步考虑预测误差中隐含的有效信息,建立区间时间序列组合...     

一般岭估计及其相对效率

讨论了下般Gauss-Markoff模型中未知参数向量的最优线形无偏估计的改造问题，引入了一般岭估计的概念且证明了其优良性，提出了关于优化无偏估计的三种估计的相对效率，并给出了它们的上界线下界。     

计算元素电离势的新方法

根据中心力场模型，应用数学插值原理发展了一种计算元素电离势的新方法，据此可根据已知元素的电离势对其它元素的电离势进行计算或预测，对200多个数据点的计算结果表明，元素电离势计算值与实验值的一致性令人满意，平均误差1.14eV.     

供应链效率损失的结构性分析

供应链效率受到结构的制约，据此，从供应链的信息和决策结构出发，分别研究在供应链内部信息对称与不对称情形下，不同的决策结构对供应链效率的影响，探讨非合作决策结构下供应链效率损失的内生性；并得出：销售商（零售商）在供应链内占据的权威越大，则该决策结构就越有效，效率损失也越小。     

一类n项和数的表达式

用Ｃｈｅｂｙｓｈｅ多项式的零点为节点的Ｌａｇｒａｎｇｅ多项式逼近高阶多项式时，误差公式中出现一类ｎ面和数。现给出此类和表达式，并用归纳法证明之。     

线性Sobolev方程的全离散间断有限体积元方法

笔者给出了线性Sobolev方程后退Euler全离散间断有限体积元格式，得到了该格式的最优L^2模和离散H^1模估计．     

Analysis of the global T_m–T_s correlation and establishment of the latitude-related linear model

In this study,the correlation between Tm,a key variable in GNSS water vapor inversion,and surface temperature(Ts)was calculated on a global scale based on the global geodetic observing system(GGOS)atmosphere Tmdata and European centre for medium-range weather forecasts(ECMWF)surface temperature data.The results show that their correlation is mainly affected by latitudes,and the correlation is stronger at high latitudes and weaker at low latitudes.Although the correlation is relatively weak in the tropic areas,the temperature changes so little in a year in these areas that we can still achieve good Tmresults by linear regression model.Based on these facts,‘‘GGOS atmosphere’’Tmdata and ECMWF Tsdata from 2005 to2011 were used to establish the global latitude-related linear regression model.The new model has root mean square error(RMSE)of 3.2,3.3,and 4.4 K,respectively,compared with respect to the‘‘GGOS atmosphere’’data,COSMIC data,and radiosonde data and is more accurate than the Bevis Tm–Tsrelationship.