1) Underdetermined Blind Source Separation
欠定盲源分离
1.
Under the sparse assumption,the problem of underdetermined blind source separation can be solved by l1-norm minimization algorithms such as the linear programming,the shortest-path algorithm,the combinatorial algo-rithm and so on.
基于稀疏假设,欠定盲源分离问题一般可采用线性规划、最短路径法和组合算法等l1范数最小化方法进行求解,但是这些传统方法对源信号的稀疏性要求较高,从而限制了源信号的估计精度。
2) Underdetermined blind separation
欠定盲分离
1.
The two-step approach is often used to separate sources in underdetermined blind separation problem.
针对目前欠定盲分离问题中源数未知,采取"两步法"进行分离源信号。
4) Underdetermined speech separation
欠定混叠语音盲分离
5) underdetermined Blind Signal Separation(BSS)
欠定的盲信号分离
6) under-determined separation
欠定分离
补充资料：盲盲
1.谓茫茫无所见。
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