给出了一种基于矩阵奇异值分解(SVD)和奇异值量化的信息隐藏算法。
An algorithm based on singular value decomposition (SVD) is proposed, which hides secret information in singular value vector.
介绍了基于动态系统可观测性矩阵奇异值分解的状态变量可观测度的分析方法。
The method of analyzing the observable degree of the state variable has been introduced by means of the singular value decomposition (SVD) of the observable matrix of a dynamic system.
主要介绍了一种典型的信噪比估计算法，并对信噪比的自相关矩阵奇异值分解估计法进行了研究。
This paper introduces a typical SNR estimation algorithm by the use of autocorrelation matrix singular value decomposition method.
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