Abstract
This correspondence develops a linear whitening transformation that minimizes the mean-squared error (MSE) between the original and whitened data, i.e.,one that results in a white output that is as close as possible to the input, in an MSE sense. When the covariance matrix of the data is not invertible, the whitening transformation is designed to optimally whiten the data on a subspace in which it is contained. The optimal whitening transformation is developed both for the case of finite-length data vectors and infinite-length signals.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
