Statistical trade-offs in modern time-frequency kernel design.
When dealing with random processes, reduced spectrum estimate variance becomes an important property which augments the list of desired time-frequency properties of modern distributions. In this paper, the degrees of freedom left in the two-dimensional kernel after satisfying the support, the marginal, and the instantaneous frequency requirements are used to yield a kernel of minimum variance. The average variance over the Nyguist interval of the spectrum estimate of a white noise process is used as the measure to be minimized. We prove that the Born-Jordan kernel [1] has the lowest possible average variance. It is also shown that the cone-shape of the modern t-f kernels is primarily responsible for their high variance. A comparison of the statistical performance of different shapes of kernels is provided.
| Main Author: | Hearon, Steven. |
|---|---|
| Other Authors: | Amin, Moeness. |
| Format: | |
| Language: | English |
| Published: |
1991
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| Online Access: |
http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:173669 |