This paper describes the preparation and properties of TiN_x-SiO_2 double-layered antireflective(AR) coatings that were applied with print process. The coating material was analyzed and TiN_x was used instead of TiO_2...This paper describes the preparation and properties of TiN_x-SiO_2 double-layered antireflective(AR) coatings that were applied with print process. The coating material was analyzed and TiN_x was used instead of TiO_2 as high refractive material. The influence of solution concentration on AR property was studied. The testing result shows that the coatings using print process are featured with excellent mechanical property and the AR property is comparable to American Southwall AR product. It is expected that the study would promote the industrialization progress in AR coatings.展开更多
P. M. Djuric, etc.(1992) researched on the segmentation of nonstationary stochastic process into piecewise stationary stochastic process by Bayesian criterion ,and gave a dynamic equation about the number of segments,...P. M. Djuric, etc.(1992) researched on the segmentation of nonstationary stochastic process into piecewise stationary stochastic process by Bayesian criterion ,and gave a dynamic equation about the number of segments, their boundaries and AR model orders for each segment, but did not give detailed solution for the equation. Because the solution for the equation is very complex, this paper investigates the solution, derives some recursive relations, simplifies the problem ,saves computation time and goes further into the segmentation of nonstationary stochastic process into piecewise stationary stochastic process.展开更多
Seismological Bureau of Sichuan Province, Chengdu 610041, China2) Center for Analysis and Prediction, State Seismological Bureau, Beijing 100036, China3) Observation Center for Prediction of Earthquakes and Volcanic E...Seismological Bureau of Sichuan Province, Chengdu 610041, China2) Center for Analysis and Prediction, State Seismological Bureau, Beijing 100036, China3) Observation Center for Prediction of Earthquakes and Volcanic Eruptions, Faculty of Sciences, Tohoku University, Sendai 98077, Japan展开更多
研究了一种新的AR SαS过程的谱估计算法。该算法将整个数据作为一个整体,利用分数低阶p阶矩从前向、后向两个方向对数据进行处理,获得了一种高分辨率的参数估计算法——双向最小p范数法(Bidirectional Least p Norm,BLPN)。利用得到的...研究了一种新的AR SαS过程的谱估计算法。该算法将整个数据作为一个整体,利用分数低阶p阶矩从前向、后向两个方向对数据进行处理,获得了一种高分辨率的参数估计算法——双向最小p范数法(Bidirectional Least p Norm,BLPN)。利用得到的参数,结合共变谱的定义,构建了AR SαS过程下的共变谱估计表达式,并分别对AR SαS过程参数估计、α稳定分布噪声中的正弦信号的谱估计进行仿真。仿真结果表明,基于BLPN的ARSαS模型的共变谱估计方法对于不同的α值均具有良好的韧性,特别是在α值较小或者短时数据时,本文方法的性能明显优于基于FLOM的AR SαS模型共变谱估计方法。展开更多
文摘This paper describes the preparation and properties of TiN_x-SiO_2 double-layered antireflective(AR) coatings that were applied with print process. The coating material was analyzed and TiN_x was used instead of TiO_2 as high refractive material. The influence of solution concentration on AR property was studied. The testing result shows that the coatings using print process are featured with excellent mechanical property and the AR property is comparable to American Southwall AR product. It is expected that the study would promote the industrialization progress in AR coatings.
文摘P. M. Djuric, etc.(1992) researched on the segmentation of nonstationary stochastic process into piecewise stationary stochastic process by Bayesian criterion ,and gave a dynamic equation about the number of segments, their boundaries and AR model orders for each segment, but did not give detailed solution for the equation. Because the solution for the equation is very complex, this paper investigates the solution, derives some recursive relations, simplifies the problem ,saves computation time and goes further into the segmentation of nonstationary stochastic process into piecewise stationary stochastic process.
文摘Seismological Bureau of Sichuan Province, Chengdu 610041, China2) Center for Analysis and Prediction, State Seismological Bureau, Beijing 100036, China3) Observation Center for Prediction of Earthquakes and Volcanic Eruptions, Faculty of Sciences, Tohoku University, Sendai 98077, Japan
文摘研究了一种新的AR SαS过程的谱估计算法。该算法将整个数据作为一个整体,利用分数低阶p阶矩从前向、后向两个方向对数据进行处理,获得了一种高分辨率的参数估计算法——双向最小p范数法(Bidirectional Least p Norm,BLPN)。利用得到的参数,结合共变谱的定义,构建了AR SαS过程下的共变谱估计表达式,并分别对AR SαS过程参数估计、α稳定分布噪声中的正弦信号的谱估计进行仿真。仿真结果表明,基于BLPN的ARSαS模型的共变谱估计方法对于不同的α值均具有良好的韧性,特别是在α值较小或者短时数据时,本文方法的性能明显优于基于FLOM的AR SαS模型共变谱估计方法。
