中国科学院机构知识库网格系统: 检索

An efficient wide area imaging scheme based on spiral scanning 会议论文 OAI收割
ELECTR NETWORK, 2022-11-24
作者: Chang, Sansan; Li, Xiang; Yang, Kai

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收藏 | 浏览/下载：10/0 | 提交时间：2023/06/19

multi lens splicing circumferential scanning method spiral dynamic scanning algorithm large area efficient imaging for airborne camera

Adaptive scale model reconstruction for radio synthesis imaging 期刊论文 OAI收割
Research in Astronomy and Astrophysics, 2021, 卷号: 21, 期号: 3, 页码: 63
作者: Zhang, L.; Mi, L. G.; Xu, L.; Zhang, M.; Li, D. Y.

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收藏 | 浏览/下载：39/0 | 提交时间：2022/06/30

methods data analysis techniques image processing techniques interferometric clean deconvolution efficient implementation algorithm Astronomy & Astrophysics

复杂无向网络连通性的一种高效判定算法 期刊论文 OAI收割
自动化学报, 2020, 卷号: 46, 期号: 10, 页码: 2129-2136
作者: 王卓; 秦博东; 徐雍; 鲁仁全; 魏庆来

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收藏 | 浏览/下载：27/0 | 提交时间：2021/02/18

Complex undirected networks graph theory connectivity multi-agent systems efficient algorithm 复杂无向网络图论连通性多智能体系统高效算法

Comparative Analysis of Energy-Efficient Scheduling Algorithms for Big Data Applications 期刊论文 OAI收割
IEEE ACCESS, 2018, 卷号: 6, 页码: 40073-40084
作者: Li, Hongjian; Wang, Huochen; Xiong, Anping; Lai, Jun; Tian, Wenhong

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收藏 | 浏览/下载：36/0 | 提交时间：2018/09/25

Big Data Deadline-constrained Energy-efficient Spark Application Tasks Scheduling Algorithm

Efficient Algorithm for Energy-Aware Virtual Network Embedding 期刊论文 OAI收割
TSINGHUA SCIENCE AND TECHNOLOGY, 2016, 卷号: 21, 期号: 4, 页码: 407-414
作者: Jia, Shuxian; Jiang, Guiyuan; He, Peilan; Wu, Jigang

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收藏 | 浏览/下载：21/0 | 提交时间：2019/12/12

virtualization technology virtual network embedding energy efficient optimization algorithm

Scheduling for energy minimization on restricted parallel processors 期刊论文 iSwitch采集
Journal of parallel and distributed computing, 2015, 卷号: 81-82, 页码: 36-46
作者: Jin, Xibo; Zhang, Fa; Fan, Liya; Song, Ying; Liu, Zhiyong

收藏 | 浏览/下载：36/0 | 提交时间：2019/05/10

Energy-efficient scheduling Restricted parallel processors Speed scaling Continuous speed model Approximation algorithm

Scheduling for energy minimization on restricted parallel processors 期刊论文 OAI收割
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2015, 卷号: 81-82, 页码: 36-46
作者: Jin, Xibo; Zhang, Fa; Fan, Liya; Song, Ying; Liu, Zhiyong

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收藏 | 浏览/下载：19/0 | 提交时间：2019/12/13

Energy-efficient scheduling Restricted parallel processors Speed scaling Continuous speed model Approximation algorithm

Novel inverse kinematic approaches for robot manipulators with Pieper-Criterion based geometry 期刊论文 OAI收割
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2015, 卷号: 13, 期号: 5, 页码: 1242-1250
作者: Liu, Huashan; Zhang Y(张阳); Zhu SQ(朱世强)

收藏 | 浏览/下载：29/0 | 提交时间：2015/10/23

Efficient algorithm inverse kinematics robot manipulator singularity

Reentry guidance based on parametric optimization (EI CONFERENCE) 会议论文 OAI收割
2012 International Conference on Mechatronics and Control Engineering, ICMCE 2012, November 29, 2012 - November 30, 2012, Guangzhou, China
作者: Li D.

收藏 | 浏览/下载：161/0 | 提交时间：2013/03/25

This paper presents a parametric optimization approach to solve reentry guidance. Due to the various constraints imposed on the trajectory original guidance problem can be converted into an optimal control problem with a merit function to be minimized. Direct implementation of method of variation and is too complex to get a reasonable result while a numerical parametric optimization approach is feasible and efficient if we choose appropriate control variables as the optimization parameters and effective optimization algorithm. A simulation of the approach is performed to show its validity on reentry guidance problem: as the value of merit function converges to acceptable threshold all constraints are hold. (2013) Trans Tech Publications Switzerland.

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：72/0 | 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.