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浏览/检索结果: 共8条，第1-8条 帮助

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Vibration control of nonlinear three-dimensional length-varying string with input quantization 期刊论文  OAI收割
JOURNAL OF VIBRATION AND CONTROL, 2020, 页码: 13
作者:  Xing, Xueyan;  Yang, Hongjun;  Liu, Jinkun;  Wang, Shuquan
  |  收藏  |  浏览/下载：47/0  |  提交时间：2020/03/30
Robust Adaptive Attitude Control for Non-rigid Spacecraft With Quantized Control Input 期刊论文  OAI收割
IEEE/CAA Journal of Automatica Sinica, 2020, 卷号: 7, 期号: 2, 页码: 472-481
作者:  Yun Li;  Fan Yang
  |  收藏  |  浏览/下载：15/0  |  提交时间：2021/03/11
Adaptive Fuzzy Output Feedback Quantized Control for Uncertain Nonlinear Hysteretic Systems Using a New Feedback-Based Quantizer 期刊论文  OAI收割
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2019, 卷号: 27, 期号: 9, 页码: 1738-1752
作者:  Wu, Honghui;  Liu, Zhi;  Zhang, Yun;  Chen, C. L. Philip
  |  收藏  |  浏览/下载：56/0  |  提交时间：2019/12/16
How much information is needed in quantized nonlinear control? 期刊论文  OAI收割
SCIENCE CHINA-INFORMATION SCIENCES, 2018, 卷号: 61, 期号: 9, 页码: 13
作者:  Zheng, Chuang;  Li, Lin;  Wang, Leyi;  Li, Chanying
  |  收藏  |  浏览/下载：36/0  |  提交时间：2018/07/30
Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs 期刊论文  OAI收割
AUTOMATICA, 2015, 卷号: 57, 页码: 113-122
作者:  Guo, Jin;  Wang, Le Yi;  Yin, George;  Zhao, Yanlong;  Zhang, Ji-Feng
  |  收藏  |  浏览/下载：27/0  |  提交时间：2018/07/30
Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文  OAI收割
4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China
作者:  Liu H.;  Liu H.;  Liu H.
收藏  |  浏览/下载：37/0  |  提交时间：2013/03/25
An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image  thus facilitating accurate diagnosis  of course at the expense of higher bit rates  i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization  wavelet coding  neural networks  and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1  or even more)  they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image  but the achievable compression ratios are only of the order 2:1  up to 4:1. In our paper  we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time  we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance  so that all the low rate codes are included at the beginning of the bit stream. Typically  the encoding process stops when the target bit rate is met. Similarly  the decoder can interrupt the decoding process at any point in the bil stream  and still reconstruct the image. Therefore  a compression scheme generating an embedded code can start sending over the network the coarser version of the image first  and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.  
A segment detection method based on improved Hough transform (EI CONFERENCE) 会议论文  OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者:  Yao Z.-J.
收藏  |  浏览/下载：24/0  |  提交时间：2013/03/25
Hough transform is recognized as a powerful tool in shape analysis which gives good results even in the presence of noise and the disconnection of edge. However  3. applying the standard Hough transform equation to every point of the input image edge  4. according to the local threshold  6. merging the segments whose extreme points are near. Experiment results show the approach not only can recognize regular geometric object but also can extract the segment feature of real targets in complex environment. So the proposed method can be used in the target detection of complicated scenes  traditional Hough transform can only detect the lines  2. quantizing the parameter space  and extracting a group of maximums according to the global threshold  eliminating spurious peaks which are caused by the spreading effects  and will improve the precision of tracking.  cannot give the endpoints and length of the line segments and it is vulnerable to the quantization errors. Based on the analysis of its limitations  Hough transform has been improved in order to detect line segment feature of targets. The algorithm aims to avoid the loss of spatial information  as well as to eliminate the spurious peaks and fix on the line segments endpoints accurately  5. fixing on the endpoints of the segments according to the dynamic clustering rule  which can expediently be used for the description and classification of regular objects. The method consists of 6 steps: 1. setting up the image  parameter and line-segment spaces  
一遍完成的平衡布点外存模型简化算法 期刊论文  OAI收割
计算机学报, 2002, 卷号: 25, 期号: 9, 页码: 936-944
蔡康颖; 王文成; 费广正; 吴恩华
  |  收藏  |  浏览/下载：17/0  |  提交时间：2011/07/29