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浏览/检索结果: 共7条，第1-7条 帮助 限定条件 内容类型：会议论文     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Neighbor-Decoding-Based Data Propagation in Vehicular Networks 会议论文 IEEE Vehicular Technology Conference, 2018-08-27 作者:  Jiang, H.;  Tang, X.;  Chen, W.;  Pu, J. 收藏  |  浏览/下载：6/0  |  提交时间：2019/12/30 Accidents  Decoding  Network coding  Coverage rate  Data collection  Data propagation  Decoding rates  Real trajectories  Transportation services  VANETs  Vehicular networks  Vehicular ad hoc networks   Research on Recognition of Forearm sEMG Signal Based on Different Motion Modes 会议论文 深圳, 2018 作者:  Zhenxin Chen;  Guanglin Li;  Shixiong Chen;  Menglong Fu;  Jinwei Xue 收藏  |  浏览/下载：60/0  |  提交时间：2019/01/31 Polar Coding for Deletion Channels: Theory and Implementation 会议论文 IEEE International Symposium on Information Theory - Proceedings 作者:  Tian, K.;  Fazeli, A.;  Vardy, A. 收藏  |  浏览/下载：8/0  |  提交时间：2019/12/30 Bit error rate  Channel capacity  Decoding  Optimal systems  Probability  Coding scheme  Computation complexity  Decoding algorithm  Deletion channels  Discrete memoryless channels  Error probabilities  Noisy channel  Symmetric information rates  Channel coding   An improvement of embedded zerotree wavelet coding based on compressed sensing 会议论文 2014 5th ieee international conference on software engineering and service science, icsess 2014, beijing, china, 2014-06-27 作者:  Chen, Zhi 收藏  |  浏览/下载：21/0  |  提交时间：2015/03/31 Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China Zhao X.; Wei J.; Zhai L.; Liu H. 收藏  |  浏览/下载：28/0  |  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.   Achievable rates and forward-backward decoding algorithms for the Gaussian relay channels under the one-code constraint 会议论文 Sydney, NSW, Australia, June 10, 2014 - June 14, 2014 作者:  Huang, Xiujie[1];  Chen, Haiqiang[2];  Ma, Xiao[3] 收藏  |  浏览/下载：1/0  |  提交时间：2019/12/23 Achievable Rates and Forward-Backward Decoding Algorithms for the Gaussian Relay Channels under the One-Code Constraint 会议论文 Sydney, AUSTRALIA, JUN 10-14, 2014 作者:  Huang, Xiujie[1];  Chen, Haiqiang[2];  Ma, Xiao[3] 收藏  |  浏览/下载：1/0  |  提交时间：2019/12/06