ID 原文 译文
22255 仿真分析表明，当行列抽样数大于信源数的两倍时，所提算法与直接基于互相关矩阵奇异值分解的非相干分布式非圆信号 DOA 估计算法性能相近，但复杂度得到了大幅度降低； The simulation results show that when the number of samples in the low-dimensional sub-matrix is larger than twice the number of sources, the performance of the proposed algorithm is comparable with the DOA estimation algorithm of incoherently distributed noncircular sources based on the singular value decomposition applying to the CC matrix.
22256 而相比于传统的低复杂度非相干分布源 DOA 估计算法，所提算法利用信号非圆特性具有更高的估计性能。 Moreover, the proposed algorithm utilizes the noncircular characteristic of the signal to achieve higher estimation performance compared with the traditional low-complexity DOA estimation algorithms of the incoherently distributed sources.
22257 准确可靠的噪声强度估计是数字图像处理领域中一个重要的研究课题。 Accurate and reliable blind noise estimation is an important research topic of digital image processing.
22258 噪声估计的难点在于如何提取用于估计的纯噪声信息，近几年，许多算法采用主成分分析技术来避免图像纹理信息的干扰，用最小特征值来估计噪声方差，可以有效地减少图像纹理信息对估计结果的影响，所以这类方法对于高频图像(丰富纹理图像)效果很好。 The main challenge is how to extract pure noise information for estimating. In recent years, many algorithms use principal component analysis technology to exclude the interference of image textures information, and estimate noise level by using the minimal eigenvalue. So that, the image textures have smallest effect on the minimal eigenvalue, thus this kind of methods performs well for high frequency image (image with abundant textures).
22259 由于图像块数量有限，最小特征值实际上比真实噪声方差小，而且图像块数量越少，偏差越大。 The minimal eigenvalue is actually smaller than the true noise variance because of limited image blocks, and the bias is the bigger if the number of image patches is the smaller.
22260 如果直接把最小特征值作为估计方差，则容易低估计高噪声。 If the noise level is estimated as the smallest eigenvalue, the final result will be underestimated.
22261 该文通过回归分析确定最小特征值跟真实噪声方差的比值和图像块数量呈幂函数关系，因此可以通过最小特征值和幂函数关系得到真实的噪声方差。 It is found that the relation between the ratio of estimated result to real noise variance and the number of image blocks is power function by using regression analysis, thus the true noise level can be computed by using the minimal eigenvalue and the power function.
22262 实验表明该文方法既能处理高频图像，又适合各种噪声水平，同时也能处理乘性高斯噪声。 The experiment results show that the proposed algorithm works well over a large range of visual content and noise conditions, and can process multiply Gaussian noise too.
22263 为有效延长水下无线传感器网络的生命周期、保持网络覆盖率，该文提出一种基于节点休眠的覆盖保持分簇算法。 A new network deployment algorithm is proposed for the problem of low network lifetime and low network coverage of underwater sensor networks.
22264 首先计算网络节点的覆盖冗余度，并对覆盖冗余度高的节点执行休眠策略，然后以网络覆盖率及节点能耗均衡性为目标，采用多目标算法进行求解，再利用 TOPSIS 法从非支配解集中选出较优解，当有节点死亡时，通过唤醒策略保持网络覆盖率。 Firstly, the node which has a higher network coverage redundancy should be asleep. Then the network coverage and energy consumption will be set as the objective functions. And the multi-objective optimization algorithm will be adopted to optimize it. At last, the TOPSIS is used to select the best solution from the Non-dominated solution set. If any node is dead, the sleeping nodes in the near dead node will be waken up to preserve the coverage.