ID |
原文 |
译文 |
47236 |
在无线网络中利用信号的全向传输特性,结合网络编码技术可以提高信道的传输效率。 |
In wireless networks, the coexistence of signal’s omnidirectional transmission characteristic and network cod-ing technique can improve the transmission efficiency in wireless channels. |
47237 |
然而无线传输过程中链路的不可靠性会造成分组传输失败,进而影响无线传输的效率。 |
However, the transmission efficiency woulddecrease due to the potential failure of packet transmissions in unreliable wireless transmission links. |
47238 |
针对该问题提出一种传输算法并且进行仿真验证。 |
To address thisproblem, a novel transmission algorithm was proposed, which was verified in the conducted network simulation. |
47239 |
该算法根据传输业务的时延要求动态管理缓存队列,并且根据网络链路状态判断是否进行基于网络编码的传输, |
Particu-larly, the proposed algorithm can dynamically manage the buffer queue according to the delay requirements of specifictransmission tasks, and decide whether encoding the transmission based on the network link status. |
47240 |
使网络的吞吐量在网络业务传输时延可接受的范围内达到最大。 |
The simulation resultsdemonstrate that the proposed algorithm can maximize the network throughout capacity with the acceptable networktransmission delay. |
47241 |
利用图像的非局部相似性先验以提升图像恢复质量已得到广泛关注。 |
Non-local similarity prior has been widely paid attention to efficiently improve image recovery quality. |
47242 |
为了更有效地提升压缩感知(CS)图像的重构质量,提出了一种基于加权结构组稀疏表示(WSGSR)的图像压缩感知重构方法。 |
Tofurther improve the recovered image quality for compressive sensing (CS), an image compressive sensing recoverymethod based on reweighted structure group sparse representation (WSGSR) was proposed. |
47243 |
采用非局部相似图像块结构组加权稀疏表示的 1l范数作为规则化项约束优化重构,实现在更好地恢复图像高频细节信息的同时有效减少对图像低频成分的损失,图像重构质量得到明显改善。 |
1l -norm of WSGSR ofimage non-local similar patch group was used as a regularization term to optimize reconstruction, which achieved wellreserving image high-frequency detail with less loss of image low-frequency component, and thus considerably improvethe reconstructed image quality. |
47244 |
推导出一种加权软阈值收缩方法,实现对模型的优化求解,对幅值较大的重要系数采用较小的阈值收缩处理,对幅值较小的非重要系数采用相对较大的阈值收缩处理。 |
A reweighted soft thresholding shrinkage method was deduced to achieve optimization solution, in which the significant coefficient with large magnitude value was shrunk by a small threshold, while thenon-significant coefficient with small magnitude value was shrunk by a relative large threshold. |
47245 |
实验结果比较验证了所提方法的有效性。 |
Experimental resultscomparison demonstrate the effectiveness of the proposed method. |