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Search Results: 1 - 10 of 92275 matches for " GUO Jun-feng "
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Using TST Constructing Biorthogonal Low Pass Multi-filters with Higher Approximation Order

Zhang Bin,Wang Jun-feng,Song Guo-xiang,

电子与信息学报 , 2003,
Abstract: This paper presents a detailed method on constructing multi-scaling functions with fractal interpolation functions, then calculates that detH0(z) and detHo(-z) have no common roots, and obtains F0(z) the dual low pass multi-filter of H0(Z) with the perfect reconstruction condition of biorthogonal low pass multi-filters. In order to construct the dual low pass multi-filter of H0(z) with higher approximation order, the two-scale similarity transform is taken for H0(z), then and its dual H0newt(z) is obtained. After applying corresponding inverse transform to F0new(z), the dual low pass multi-filter of H0(z) with higher approximation order is achieved.
Ecosystem services of wetlands and their delineation in China

ZHAO Qi-Guo,GAO Jun-Feng,

中国生态农业学报 , 2007,
Abstract: 湿地在调节气候、调蓄水量、净化水体、保持水土、生物多样性保护及文化休闲等方面具有重要作用。本文分析了中国湿地的现状、分布与存在问题,并根据湿地的生态系统服务功能,将中国湿地划分成3个一级区,7个二级区,为制定湿地生态环境保护与建设规划、维护湿地生态安全、合理利用湿地资源与生产布局提供依据。
Grey Prediction Based Particle Filter for Maneuvering Target Tracking
Jun-Feng Chen;Zhi-Guo Shi;Shao-Hua Hong;Kang Sheng Chen
PIER , 2009, DOI: 10.2528/PIER09042204
Abstract: For maneuvering target tracking, we propose a novel grey prediction based particle filter (GP-PF), which incorporates the grey prediction algorithm into the standard particle filter (SPF). The basic idea of the GP-PF is that new particles are sampled by both the state transition prior and the grey prediction algorithm. Since the grey prediction algorithm is a kind of model-free method and is able to predict the system state based on historical measurements other than establishing a priori dynamic model, the GP-PF can significantly alleviate the sample degeneracy problem which is common in SPF, especially when it is used for maneuvering target tracking. Simulations are conducted in the context of two typical maneuvering motion scenarios and the results indicate that the overall performance of the proposed GP-PF is better than the SPF and the multiple model particle filter (MMPF) when the tracking accuracy, computational complexity and tracking lost probability are considered. The performance improvements can be attributed to that the GP-PF has both model-based and model-free features.
An Efficient Digital Ink Multi-Dimension Data Coding Algorithm

LI Jun-Feng,DAI Guo-Zhong,

软件学报 , 2006,
Abstract: An efficient digital ink data coding algorithm IWPHSP (integer wavelet packet based hierarchical set partitioned) is proposed in this paper. The algorithm compresses digital ink multi-dimension data losslessly using three approaches: integer wavelet packet transform, hierarchical set partitioned, significant bits combination code and fast adaptive arithmetic code. The experiments show that the IWPHSP algorithm is efficient.
Fuzzy-Control-Based Particle Filter for Maneuvering Target Tracking
Xianfeng Wang;Jun-Feng Chen;Zhi-Guo Shi;Kang Sheng Chen
PIER , 2011, DOI: 10.2528/PIER11051907
Abstract: In this paper, we propose a novel fuzzy-control-based particle filter (FCPF) for maneuvering target tracking, which combines the advantages of standard particle filter (SPF) and multiple model particle filter (MMPF). That is, the SPF is adopted during non-maneuvering movement while the MMPF is adopted during maneuvering movement. The key point of the FCPF is to use a fuzzy controller, which could imitate the thoughts of human beings in some degree, to detect the target's maneuver and use a backward correction sub-algorithm to alleviate the performance degradation of MMPF caused by detection delay. Simulation results indicate that the proposed algorithm has a much better tracking accuracy than the SPF while keeps approximately equal computational complexity. Compared with MMPF, both algorithms have no tracking lost, but the tracking accuracy of the proposed FCPF is a little better than the MMPF, and the FCPF consumes about 66% computation time of the MMPF. Thus, the proposed algorithm offers a more effective way for maneuvering target tracking.
Huayou Hu,Lei Li,Jun-Feng Ji,Zhi-Guo Shen
Acta Crystallographica Section E , 2008, DOI: 10.1107/s1600536808031139
Abstract: The title compound, C20H10Cl6O2, a quinone derivative, was obtained by the irradiation of 2,3,5,6-tetrachlorobenzoquinone and 4,4′-(ethene-1,1-diyl)bis(chlorobenzene). The six- and four-membered rings are fused in a cis configuration. The dihedral angle between them is 53.4 (3)°.
FastMatch:an efficient algorithm for XML keyword search

CUI Jian,ZHOU Jun-feng,GUO Jing-feng,
崔 健

计算机应用研究 , 2012,
Abstract: Existing methods of XML keyword search need firstly identify qualified root nodes satisfying specified semantics, then construct subtree results that meet some certain conditions. Such a strategy needs to process all nodes in the inverted lists more than once, so it is inefficient in practice. To solve this problem, this paper proposed a method used fast group to reduce the times of scaning the inverted lists, then proposed a algorithm named FastMatch based on the method.This algorithm found all subtree results meeting some certain conditions by scanning all nodes in the inverted lists only once. The experimental results verify the high performance of this method.
Adaptive Wavelet Thresholding for Image Denoising

SHANG Xiao-Qing WANG Jun-Feng SONG Guo-Xiang,

计算机科学 , 2003,
Abstract: Selecting threshold is the most important in threshold.based nonlinear filtering by wavelet transform. In this paper, a novel adaptive threshold is proposed by minimizing a Bayesian risk (It is adaptive to subband because it depends on data-driven estimates of the parameters). Combining this thresholding method with Wiener filting can result a new denoising method. Expermental results show that the proposed method indeed remove noise significantly and retaining most image edges. The results compare favorably with the reported results in the recent denoising literature.
A New Nonlinear Adaptive Equalizer Based on Combined Neural Networks

WANG Jun-Feng ZHANG Bin SONG Guo-Xiang,

计算机科学 , 2003,
Abstract: A new nonlinear decision feedback adaptive equalizer based on Adaline neural network and radial-basis-function neural network is presented. Its structure and algorithm are also investigated. For a typical linear and nonlinear channel models, computer simulation shows that its convergence speed is faster and its stable mean square error is less.
Furfural residues from straw become complex fertilizer by addition method
LIU Jun,|feng,YI Ping,|gui,CHEN An,|guo,
LIU Jun-feng
,YI Ping-gui,XIAO He-lian

环境科学学报(英文版) , 2000,
Abstract: The additives such as phosphoric acid, calcium phosphate,calcium super phosphate, calcium over-super phosphate, calcium carbonate, sodium hydrosulphite, etc. were used to produce furfural from the straw by hydrolysis with sulfuric acid. The effect of amount of the additives, the content of the added substance and the conditions of distillation on the acidity of the residues were studied. The experiment results showed that the all residues become neutral complex fertilizer, and the productivity of furfural increases under the following conditions: sulfuric acid concentration is 20% (by weight), the ratio of liquid to solid is 3:1--4:1 (by weight), the ratio of the additives to straw is suitable.
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