A modified ULV updating algorithm. is applied to performing noise subspace tracking. The algorithm does not require rank estimation of the correlation matrix, and estimate directly the noise subspace.

使用一种修改的ULV更新算法进行噪声子空间跟踪，该算法不需要相关矩阵的秩估计，直接估计噪声子空间。

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With an appropriate state space neighbour for the nonlinear local analysis, the short_delay predictor is also able to effectively model the long_term correlation without pitch estimation.

用合适的状态空间邻近矢量进行非线性局部分析，即使没有基音周期估计，短时预测器同样能建立长时相关性模型。

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The data correlation and state estimation are both certainly independent and closely relative, but the performance of tracking systems can be improved by suitable incorporating the two components.

数据关联和目标状态估计两部分既有一定的独立性又有密切的联系，而将两部分合理地结合对提高跟踪系统的性能是重要的。

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