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	Detection of Periodic Signals With Time-Varying Coefficients From CMONOC Stations in China by Singular Spectrum Analysis 期刊论文 OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61, 页码: 5802812 作者: Wu, Shuguang; Li, Zhao; Li, Houpu; Bian, Shaofeng; Ouyang, Hua \| 收藏 \| 浏览/下载：15/0 \| 提交时间：2024/01/04 Crustal Movement Observation Network of China (CMONOC) stations periodic signals with time-varying coefficients (PSTC) root mean square error (RMSE) improve-ment rate singular spectrum analysis (SSA) method
	Brownness of Organic Aerosol over the United States: Evidence for Seasonal Biomass Burning and Photobleaching Effects 期刊论文 OAI收割 ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2021, 卷号: 55, 期号: 13, 页码: 8561-8572 作者: Chen, Lung-Wen Antony; Chow, Judith C.; Wang, Xiaoliang; Cao, Junji; Mao, Jingqiu \| 收藏 \| 浏览/下载：68/0 \| 提交时间：2021/12/06 brown carbon black carbon white carbon aerosol aging IMPROVE network hybrid environmental receptor model
	Research and optimization on media access control delay of CAN (EI CONFERENCE) 会议论文 OAI收割 2012 International Conference on Information Technology and Management Innovation, ICITMI 2012, November 10, 2012 - November 11, 2012, Guangzhou, China 作者: Zhang H.; Zhang W.; Zhang W.; Zhang H. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 With data quantity increasing dramatically and signal transmission period becoming more and more fast the media access control delay has proved to be one of the main influence factors of CAN network real-time. Firstly an equivalent numerical simulation model of CAN bus network is built to derivate the mathematical expression of media access control delay. Secondly optimization measures are further proposed to improve the data communication real-time. At last the optimization measures tested by experiments are proved to be correct and effective. (2013) Trans Tech Publications Switzerland.
	An improved hyperspectral classification algorithm based on back-propagation neural networks (EI CONFERENCE) 会议论文 OAI收割 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China 作者: Yu P.; Yu P. 收藏 \| 浏览/下载：37/0 \| 提交时间：2013/03/25 In this paper a new method is proposed to improve the classification performance of hyperspectral images by combining the principal component analysis (PCA) genetic algorithm (GA) and artificial neural networks (ANNs). First some characteristics of the hyperspectral remotely sensed data such as high correlation high redundancy etc. are investigated. Based on the above analysis we propose to use the principal component analysis to capture the main information existing in the hyperspectral images and reduce its dimensionality consequently. Next we use neural networks to classify the reduced hyperspectral data. Since the back-propagation neural network we used is easy to suffer from the local minimum problem we adopt a genetic algorithm to optimize the BP network's weights and the threshold. Experimental results show that the classification accuracy is improved and the time of calculation is reduced as well. 2012 IEEE.
	Study on time registration method for photoelectric theodolite data fusion (EI CONFERENCE) 会议论文 OAI收割 10th World Congress on Intelligent Control and Automation, WCICA 2012, July 6, 2012 - July 8, 2012, Beijing, China Yang H.-T.; Gao H.-B. 收藏 \| 浏览/下载：19/0 \| 提交时间：2013/03/25 In range measurement theodolite and radar constitute a real-time tracking system at different sites to track the same target in the air and get useful information exactly and timely. As the optical theodolite and radar have different sampling frequency and measurement system the data is sent to the fusion center is asynchronous. This paper proposed a time registration method based on multi-sensor data using Wavelet neural network algorithm which not only better solved the basic problems of theodolite fusion tracking but also improve the efficiency of data fusion. Simulation experiment and comparison with other time registration method have shown the advantage of this method. 2012 IEEE.
	An approach to the misleading action solving in plan recognition (EI CONFERENCE) 会议论文 OAI收割 2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012, July 15, 2012 - July 17, 2012, Xian, Shaanxi, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：20/0 \| 提交时间：2013/03/25 Misleading actions have not been considered in previous researches on plan recognition. It leads to poor recognition results for some special domains. This paper introduces new concepts including reliability correlativity and correlated action sequence etc. A novel algorithm is proposed to recognize a misleading action by using correlated action sequences. The proposed algorithm is shown to improve the accuracy of plan recognition. Moreover it could also be applied to intrusion detection and network security problems. 2012 IEEE.
	Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China Wu Z.-G.; Wang M.-J.; Han G.-L. 收藏 \| 浏览/下载：78/0 \| 提交时间：2013/03/25 Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.
	Research on the identification for a nonlinear system (EI CONFERENCE) 会议论文 OAI收割 International Conference on Optical, Electronic Materials and Applications 2011, OEMA 2011, March 4, 2011 - March 6, 2011, Chongqing, China 作者: Liu J.; Jia P.; Liu J.; Liu J. 收藏 \| 浏览/下载：35/0 \| 提交时间：2013/03/25 The characteristic of the drift error of inertial platform is a high-order nonlinear dynamic system using the neural networks' abilities of universal approximation of differentiable trajectory and capturing system dynamic information this paper presents the drift error identifying project of inertial platform based on Elman networks structure. First the drift error model of inertial platform is established after selecting the input and output for network momentum and alterable speed algorithm is used to speed up the network convergence. On the basis of the algorithm the extended nonlinear node function in the hidden network does not only improve the learning speed of network but also satisfies the need of accuracy on system identification. Through the drift error data measured on inertial platform the training result shows that the scheme achieves satisfied identification results. (2011) Trans Tech Publications.
	Study of adaptive inverse control to stale platform (EI CONFERENCE) 会议论文 OAI收割 International Conference on Computer Science and Software Engineering, CSSE 2008, December 12, 2008 - December 14, 2008, Wuhan, Hubei, China 作者: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：25/0 \| 提交时间：2013/03/25 Stable platform is a complicated nonlinear system. The common PID control can not meet the requirement of high precision and fast response. The adaptive inverse control was introduced in the system of stable platform. Based on it the system utilize its character of open circle to improve system capability. In the model building to object model and object inverse model the NARX network is used. The algorithm uses the least square method instead of least square(LMS) to identify the parameters and design the control. The simulation results show several advantages of this control strategy such as sensitive response non-overshoot good anti-disturbance and minimal stable error and showed dynamic/static performance was superior to those of conventional PID method. 2008 IEEE.