The least squares solution of inverse problems of generalized skew symmetric matrices and It's optimal approximation problems are discussed.
讨论了线性流形上广义次对称矩阵反问题的最小二乘解及其逼近问题。
For both problems, we study their computational complexity and present optimal algorithms or polynomial time approximation algorithms.
并且对这两类问题都研究了他们的计算复杂性并给出了最优算法或者多项式时间近似算法。
Signal sparse representation or the optimal N-term approximation is one of the important problems, which is applied to many areas such as the data compression, denoising.
信号的稀疏表示或最佳n -项逼近是数据压缩、噪声抑制等众多应用中的一个重要问题。
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