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41.
日冕物质抛射(Coronal Mass Ejection,CME)参数识别模型是太阳风预报过程的重要组成部分.在空间环境预报业务中,为提高太阳风预报的准确率,需要提高CME参数识别的精度.模型以计算任务串行的方式运行,运算效率低导致模型运算时间长,不能满足这种需求.CME参数识别模型的物理运算过程相互不独立,其在单节点上的运行方式不能满足并行化要求.基于MapReduce的并行计算框架,改进了CME参数识别模型的计算流程,提出CDMR(CME detection under MapReduce)方法,实现了CME参数识别模型的并行计算,并对比分析CME参数识别模型在串行计算和MapReduce并行计算下的运行时间,提高了模型的识别精度和计算效率. 相似文献
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本文提出了一种基于虚拟页地址映射的NAND Flash管理算法.该算法通过定义坏块表、对应表等结构,以及设计的坏块替换策略和虚拟页地址到实际物理页地址的转换算法,实现上层软件采用虚拟地址对NAND Flash的无坏块连续页地址访问.该算法是一种高效的地址映射算法,能高效地对数据进行索引,占用SRAM空间较少,使系统达到高性能,并使得闪存使用的更加稳定持久. 相似文献
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《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2020,65(1):560-571
The precise point positioning (PPP) technique is widely used in time and frequency applications. Because of the real-time service (RTS) project of the International GNSS Service, we can use the PPP technique for real-time clock comparison and monitoring. As a participant in the RTS, the Centre National d’Etudes Spatiales (CNES) implements the PPPWIZARD (Precise Point Positioning with Integer and Zero-difference Ambiguity Resolution Demonstrator) project to validate carrier phase ambiguity resolution. Unlike the Integer-PPP (IPPP) of the CNES, fixing ambiguities in the post-processing mode, the PPPWIZARD operates in the real-time mode, which is also called real-time IPPP (RT-IPPP). This paper focuses on applying the RT-IPPP for real-time clock comparison and monitoring. We review the principle of real-time clock comparison and monitoring, and introduce the methodology of the RT-IPPP technique. The observations of GPS, GLONASS and Galileo were processed for the experiments. Five processing modes were provided in the experiment to analyze the benefits of ambiguity resolution and multi-GNSS. In the clock comparison experiment, the average reduction ratios of standard deviations with respect to the G PPP mode range from 9.7% to 35.0%. In the clock monitoring experiment, G PPP mode can detect clock jumps whose magnitudes are larger than 0.9 ns. The RT-IPPP technique with GRE PPP AR (G) mode allows for the detection of any clock jumps larger than 0.6 ns. For frequency monitoring, G PPP mode allows detection of frequency changes larger than 1.1 × 10−14. When the RT-IPPP technique is applied, monitoring with GRE PPP AR (G) mode can detect frequency changes larger than 6.1 × 10−15. 相似文献
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为了解决传统目标检测中遇到的检测速度慢、精度低等问题,本文提出一种新的图像特征——相对最值点,并依据相对最值点提出一种新的最小二乘直线检测的方法。该方法首先搜索Canny边缘的闭合包络,并寻找闭合包络的相对最值点。包络上相邻相对最值点之间长度满足阈值要求的即为疑似直线的两端点,进而利用最小二乘拟合方法获得该疑似直线的拟合方差,最后利用拟合方差与拟合直线长度之比作为直线判定的标准用来检测出图像中的直线。实验表明,本方法与传统方法如PPHT直线检测、LSD直线检测方法等相比,检测直线的精度更高,检测速度更快。 相似文献
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目标检测与跟踪技术广泛应用于交通、医疗、安保和航天等领域.目前,目标检测与跟踪技术面临目标微弱、背景复杂、目标被遮挡等挑战.同时,随着脑科学研究的不断深入,人们对人脑视觉系统的理解逐渐透彻,利用类脑计算解决复杂背景下高精度目标检测与跟踪问题成为相关领域的重要研究方向.本文结合神经工程导向的类脑模型和计算机工程导向的深度神经网络(Deep Neural Networks, DNNs),提出多种基于类脑模型与深度神经网络的目标检测与跟踪算法,包括:基于演算侧抑制的目标检测算法,基于结构 对比度(Structure Contrast, SC)视觉注意模型的弱小目标检测算法和基于记忆机制与分层卷积特征的目标跟踪算法.实验结果表明,将类脑模型和深度神经网络应用于目标检测和跟踪领域,有利于实现复杂条件下的高精度目标检测和鲁棒性目标跟踪. 相似文献
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《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2020,65(1):86-94
We have studied the time delay of ionospheric storms to geomagnetic storms at a low latitude station Taoyuan (25.02°N, 121.21°E), Taiwan using the Dst and TEC data during 126 geomagnetic storms from the year 2002 to 2014. In addition to the known local time dependence of the time delay, the statistics show that the time delay has significant seasonal characteristics, which can be explained within the framework of the seasonal characteristics of the ionospheric TEC. The data also show that there is no correlation between the time delay and the intensity of magnetic storms. As for the solar activity dependence of the time delay, the results show that there is no relationship between the time delay of positive storms and the solar activity, whereas the time delay of negative storms has weakly negative dependence on the solar activity, with correlation coefficient −0.41. Especially, there are two kinds of extreme events: pre-storm response events and long-time delay events. All of the pre-storm response events occurred during 15–20 LT, manifesting the Equator Ionospheric Anomaly (EIA) feature at Taoyuan. Moreover, the common features of the pre-storm response events suggest the storm sudden commencement (SSC) and weak geomagnetic disturbance before the main phase onset (MPO) of magnetic storms are two main possible causes of the pre-storm response events. By analyzing the geomagnetic indices during the events with long-time delay, we infer that this kind of events may not be caused by magnetic storms, and they might belong to ionospheric Q-disturbances. 相似文献