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| 1 | 基于正交秩-1矩阵追踪的天然地震数据重建研究:以加州San Jacinto断层密集地震台阵为例显示文摘由于受地理环境和采集成本等因素的影响,采集到的天然地震数据往往呈现不规则和不完整分布,将直接影响到后续的天然地震数据处理效果,因此需要对缺失数据进行重建.本文将一种基于降秩补全理论的正交秩-1矩阵追踪算法(Orthogonal Rank-One Matrix Pursuit,OR1MP)应用于加州San Jacinto断层带的天然地震数据重建.首先将空间数据的每个频率切片进行Hankel预变换,获取具有低秩结构特征的预变换矩阵,缺失地震道和随机噪声会增加数据预变换矩阵的秩,然后运用OR1MP算法进行降秩处理,最后做反Hankel变换,得到频域上的重建数据.OR1MP算法对2D和3D的加州San Jacinto断层带的天然地震数据实验结果表明,OR1MP算法能够有效地增加地震体的峰值信噪比,能较好地实现对天然地震信号的重建. | 张雪敏 付丽华 张海江 彭佳明 | 2019 | 地球物理学报2019，62，4： | 3 |
| 2 | 基于奇异谱分析的BDS卫星钟差周期项提取显示文摘在建立星座自主时间基准时,必须扣除卫星钟差的周期波动,以避免将其引入系统时间。为准确地扣除周期波动,提出一种基于奇异谱分析(SSA)的BDS卫星钟差周期项提取方法。首先,经SSA分解获得钟差信号的多个重构成分;然后,引入重标极差分析方法计算各重构成分的Hurst指数,根据Hurst指数辨识钟差的低频信号主导分量和高频信号随机分量,从而实现周期项的重建提取。对不同类型的BDS卫星钟进行了分析和研究,结果表明:所提方法能够准确提取钟差周期项,所提取周期项的频谱特征比钟差多项式拟合残差的频谱更为清晰;利用多项式拟合方法扣除周期项后,万秒稳和日稳平均分别提升4.1%和2.4%,而利用所提方法扣除周期项后,万秒稳和日稳平均分别提升20.9%和34.1%,提高了卫星钟频率稳定度,为星座自主时间基准的建立提供了基础。 | 雷雨 赵丹宁 | 2023 | 中国惯性技术学报2023，31，9： | 2 |
| 3 | EXCHANGE RATE FORECASTING WITH OPTIMUM SINGULAR SPECTRUM ANALYSIS显示文摘 | GHODSI Mansi YARMOHAMMADI Masoud | 2014 | Journal of Systems Science & Complexity2014，27，1： | 2 |
| 4 | ESTIMATING MULTI-COUNTRY PROSPERITY INDEX: A TWO-DIMENSIONAL SINGULAR SPECTRUM ANALYSIS APPROACH显示文摘 | ZHANG Jiawei HASSANI Hossein XIE Haibin ZHANG Xun (Corresponding author) | 2014 | Journal of Systems Science & Complexity2014，27，1： | 2 |
| 5 | 基于奇异谱的桥梁高索塔位移GPS-RTK监测技术显示文摘为研究桥梁高索塔的变形趋势和震荡周期,将奇异谱分析(SSA)应用到苏通大桥高索塔RTK监测位移时间序列中。该方法有效提取序列中趋势周期振荡成分,春夏两季塔尖向S方向偏移,秋冬两季索塔塔尖向N方向偏移,偏移速度为7.46mm/月,桥梁索塔振荡周期为12个月;对重建的主成分进行加权相关系数检验,各成分独立性很强,主成分分组得到重建序列均方误差和残差中误差达到mm级,起到了降噪平滑效果。 | 曹奇 岳东杰 韩易 王性猛 | 2014 | 勘察科学技术2014，，2： | 1 |
| 6 | FORECASTING EXCHANGE RATES: AN OPTIMAL APPROACH显示文摘 | BENEKI Christina YARMOHAMMADI Masoud | 2014 | Journal of Systems Science & Complexity2014，27，1： | 0 |
| 7 | Smoothing Non-Stationary Time Series Using the Discrete Cosine Transform显示文摘This paper considers the problem of smoothing a non-stationary time series(having either deterministic and/or stochastic trends) using the discrete cosine transform(DCT).The DCT is a powerful tool which has found fruitful applications in filtering and smoothing as it can closely approximate the optimal Karhunen-Loeve transform(KLT).In fact,it is known that it almost corresponds to the KLT for first-order autoregressive processes with a root close to unity:This is the case with most economic and financial time series.A number of new results are derived in the paper:(a) The explicit form of the linear smoother based on the DCT,which is found to have time-varying weights and that uses all observations;(b) the extrapolation of the DCT-smoothed series;(c) the form of the average frequency response function,which is shown to approximate the frequency response of the ideal low pass filter;(d) the asymptotic distribution of the DCT coefficients under the assumptions of deterministic or stochastic trends;(e) two news method for selecting an appropriate degree of smoothing,in general and under the assumptions in(d).These findings are applied and illustrated using several real world economic and financial time series.The results indicate that the DCT-based smoother that is proposed can find many useful applications in economic and financial time series. | THOMAKOS Dimitrios | 2016 | Journal of Systems Science & Complexity2016，29，2： | 0 |
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