deposit_your_work

An Adaptive Optimal-Kernel Time-Frequency Representation

Files in this item

Files Size Format View
Jon1995Oct5AnAdaptiv.PDF 1.038Mb application/pdf Thumbnail
Jon1995Oct5AnAdaptiv.PS 3.385Mb application/postscript View/Open

Show full item record

Item Metadata

Title: An Adaptive Optimal-Kernel Time-Frequency Representation
Author: Jones, Douglas L.; Baraniuk, Richard G.
Type: Journal Paper
Keywords: Temporary
Citation: D. L. Jones and R. G. Baraniuk, "An Adaptive Optimal-Kernel Time-Frequency Representation," IEEE Transactions on Signal Processing, vol. 43, no. 10, pp. 2361-2371, 1995.
Abstract: Time-frequency representations with fixed windows or kernels figure prominently in many applications, but perform well only for limited classes of signals. Representations with signal- dependent kernels can overcome this limitation. However, while they often perform well, most existing schemes are block-oriented techniques unsuitable for on-line implementation or for tracking signal components with characteristics that change with time. The time-frequency representation developed here, based on a signal-dependent radially Gaussian kernel that adapts over time, overcomes these limitations. The method employs a short-time ambiguity function both for kernel optimization and as an intermediate step in computing constant-time slices of the representation. Careful algorithm design provides reasonably efficient computation and allows on-line implementation. Certain enhancements, such as cone-kernel constraints and approximate retention of marginals, are easily incorporated with little additional computation. While somewhat more expensive than fixed-kernel representations, this new technique often provides much better performance. Several examples illustrate its behavior on synthetic and real-world signals.
Date Published: 1995-10-01

This item appears in the following Collection(s)

  • ECE Publications [1032 items]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508 items]
    Publications by Rice Faculty and graduate students in digital signal processing.