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	基于时变模型平均方法的我国航空客运量预测期刊论文 OAI收割系统工程理论与实践, 2020, 卷号: 40, 期号: 6, 页码: 1509-1519 作者: 张健; 孙玉莹; 张新雨; 汪寿阳 \| 收藏 \| 浏览/下载：56/0 \| 提交时间：2021/01/14 air passengers time-varying model average non-parametric estimation time-varying weights time-varying parameter predictive models 航空客运量时变模型平均非参数估计时变权重时变参数预测模型
	A real-time, high-accuracy, hardware-based integrated parameter estimator for deep space navigation and planetary radio science experiments 期刊论文 OAI收割 MEASUREMENT SCIENCE AND TECHNOLOGY, 2019, 卷号: 30, 期号: 1, 页码: 015007 作者: Zhou, Chenye; Wang, Zhen; Li, Wenxiao; Wang, Mingyuan; Yu, Quantao \| 收藏 \| 浏览/下载：112/0 \| 提交时间：2019/03/04 planetary radio science non-stationary signal processing narrowband signal parameter estimation FPGA
	A real-time, high-accuracy, hardware-based integrated parameter estimator for deep space navigation and planetary radio science experiments 期刊论文 OAI收割 MEASUREMENT SCIENCE AND TECHNOLOGY, 2019, 卷号: 30, 期号: 1, 页码: 12 作者: Zhang, Tianyi; Meng, Qiao; Ping, Jinsong; Chen, Congyan; Jian, Nianchuan \| 收藏 \| 浏览/下载：68/0 \| 提交时间：2019/05/23 planetary radio science non-stationary signal processing narrowband signal parameter estimation FPGA
	A real-time, high-accuracy, hardware-based integrated parameter estimator for deep space navigation and planetary radio science experiments 期刊论文 OAI收割 MEASUREMENT SCIENCE AND TECHNOLOGY, 2019, 卷号: 30, 期号: 1, 页码: 12 作者: Zhang, Tianyi; Meng, Qiao; Ping, Jinsong; Chen, Congyan; Jian, Nianchuan \| 收藏 \| 浏览/下载：31/0 \| 提交时间：2020/03/10 planetary radio science non-stationary signal processing narrowband signal parameter estimation FPGA
	The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Sun H.; Han H.-X.; Sun H. 收藏 \| 浏览/下载：60/0 \| 提交时间：2013/03/25 Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	A high-accuracy parameter estimation algorithm for jointless Frequency-shift track circuit (EI CONFERENCE) 会议论文 OAI收割 ISECS International Colloquium on Computing, Communication, Control, and Management, CCCM 2008, August 3, 2008 - August 4, 2008, Guangzhou, China 作者: Zheng X. 收藏 \| 浏览/下载：25/0 \| 提交时间：2013/03/25 FSK (Frequency Shift keying) signal which has advantages of narrow-bandwidth strong anti-interference ability long transmission distance and so on is used in jointless Frequency-shift track circuit to send different kinds of control signals. However as FSK is non-linearly modulated parameter estimation with high accuracy is hard to realize. Based on the spectrum analysis complement with time-frequency distribution a highaccuracy FSK signal parameter estimation algorithm is put forward in this paper. According to the signal characteristics under-sampling and ZFFT are used to improve the accuracy of spectrum analysis and the base frequency resolution meets system requirement of 0.02Hz. Wigner-Ville distribution has an excellent time-frequency concentration while serious cross-term interference at the same time. Through the design of kernel function the cross-terms are almost suppressed and the upper/down side frequency resolution meets the system requirement of 0.2Hz. The effectivities of all the methods mentioned above have been proved by MATLAB simulation which pave a solid way for the development of high-accuracy FSK signal parameter estimation devices. 2008 IEEE.
	Non-parameter estimation algorithm to determine stellar effective temperature 期刊论文 OAI收割 SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 卷号: 25, 期号: 12, 页码: 2088-2091 作者: Zhang, JN; Wu, FC; Luo, AL; Zhao, YH 收藏 \| 浏览/下载：19/0 \| 提交时间：2015/11/06 stellar spectrum effective temperature of star non-parameter estimation PCA