Time-frequency distribution kernel design over a discrete powers-of-two space.
We introduce a new class of powers-of-two (PFT) kernels for fast real-time implementations of time-frequency (t-f) distributions. In this class, the local autocorrelation function is computed using a series of shifting and addition operations. PFT filter design techniques can be applied to produce fixed kernels or to design data-dependent kernels suitable for specific operating environments. In the t-f context, where the task is to identify the signal autoterms in the t-f domain, a discretized PFT kernel shows little or no difference in performance from its infinite precision counterpart.
| Main Author: | Venkatesan, Gopal T. |
|---|---|
| Other Authors: | Amin, Moeness G. |
| Format: | |
| Language: | English |
| Published: |
1996
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| Online Access: |
http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:173747 |