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Eigenvalue/Eigenvector Interpretation of Surface Reverberation Rejection Performance

机译:表面混响抑制性能的特征值/特征向量解释

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The application of adaptive least-mean square (LMS) and least squares lattice (LSL) algorithms to the rejection of sea surface reverberation is discussed. A specific dual channel noise cancelling structure is considered along with the results of processing a ping selected from an experimental ocean reverberation data set. A time evolving eigenvalue/eigenvector decomposition is used to provide insight into the performance differences between the two adaptive algorithms in the highly dynamic physical geometry.

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