Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4977537 | Signal Processing | 2017 | 48 Pages |
Abstract
We propose and justify new transforms of random vectors which provide, under a certain condition, better associated accuracy than that of the optimal transforms, the generic Karhunen-Loève transform and the transform considered by Brillinger. It is achieved by special structures of the proposed transforms which contain more parameters to optimize compared to the known transforms.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Pablo Soto-Quiros, Anatoli Torokhti,