摘要
Covariance, one of the most widely accepted mathematical tool for similarity measurement relies heavily on the assumption of Gaussian distribution noise model. Along with many other second-order statistics based methods, its performance deteriorates significantly in the presence of impulsive noise. Therefore, in this study, a generalised covariance function named bounded non-linear covariance (BNC) is put forward to handle relative problems in the presence of noise with non-Gaussian and heavy-tailed distribution. Meanwhile, the projection approximation subspace tracking-like algorithm based on BNC is proposed as well. Simulations have verified its performances over existing methods, especially the robustness to impulsive noise.
- 出版日期2017-7
- 单位大连理工大学