Recursive kernels for time-frequency signal representations.

Time-frequency distribution kernels which satisfy the desirable time-frequency properties and simultaneously allow recursive implementations of the local autocorrelation and the ambiguity functions are computationally efficient and prove valuable for on-line processing. We introduce a class of recursive kernels which apply modified comb filters at different timelags. The generalized Hamming, Blackman, and Half-Sine kernels are members of this class. These kernels have well known lowpass filter characteristics, lead to computational invariance under the kernel extent, and compete in performance with existing nonrecursive t-f kernels.

Main Author: Amin, Moeness G.
Format: Villanova Faculty Authorship
Language: English
Published: 1996
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