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CORC

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Step-by-step classification detection algorithm of SPPM based on K-means clustering 期刊论文
Tongxin Xuebao/Journal on Communications, 2022, 卷号: 43, 期号: 1, 页码: 161-171
作者:  Wang, Huiqin;  Hou, Wenbin;  Peng, Qingbin;  Cao, Minghua;  Huang, Rui
收藏  |  浏览/下载：12/0  |  提交时间：2022/04/21
Enhanced Optical Spatial Modulation in Wireless Optical Communication 期刊论文
Guangxue Xuebao/Acta Optica Sinica, 2020, 卷号: 40, 期号: 3
作者:  Zhang, Yue;  Wang, Huiqin;  Cao, Minghua;  Huang, Rui
收藏  |  浏览/下载：17/0  |  提交时间：2020/11/14
Reversible video data hiding using zero QDCT coefficient-pairs 期刊论文
MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 卷号: 78, 期号: 16, 页码: 23097-23115
作者:  Chen, Yi;  Wang, Hongxia;  Wu, Hanzhou;  Liu, Yong
收藏  |  浏览/下载：70/0  |  提交时间：2019/12/16
On implicit integration of the bounding surface model based on swell-shrink rules 期刊论文
APPLIED MATHEMATICAL MODELLING, 2016, 卷号: 40, 期号: 19-20, 页码: 8671-8684
作者:  Li, Jian;  Chen, Shanxiong;  Jiang, Lingfa
收藏  |  浏览/下载：10/0  |  提交时间：2018/06/05
An identification method for process abnormal fluctuation source based on brittleness network and its application 会议论文
作者:  Diao, Guangzhou;  Zhao, Liping;  Yao, Yiyong
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/02
Bidirectional structural mapping models for constructing rule-based systems 会议论文
31st Chinese Control Conference, CCC 2012, Hefei, China, July 25, 2012 - July 27, 2012
作者:  Yuan J(袁杰);  Shang WL(尚文利);  Jiang B(姜波);  Lou, Yi
收藏  |  浏览/下载：14/0  |  提交时间：2013/04/21
Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文
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：31/0  |  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.  
Structure analysis and function evaluation of a kind of fuzzy PID controllers 期刊论文
2010, 2010
Du Xinyu; Zhang Naiyao; Yu Na
收藏  |  浏览/下载：2/0

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