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. The authors introduce a class...

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Journal Title: IEEE Signal Processing Letters Vol. 3; no. 1; pp. 16 - 18
Author: Moeness Amin
Format: Article
Published: Jan 1996
Subjects:
Online Access: Full Text
Summary: 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. The authors 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 low-pass filter characteristics, lead to computational invariance under the kernel extent, and compete in performance with existing nonrecursive t-f kernels.
ISSN: 1558-2361