Signal reconstruction from nonuniformly spaced samples using evolutionary Slepian transform-based POCS

Authors:
Jinsung Oh;Seda Senay;Luis F. Chaparro
Affiliations:
Department of Electrical Engineering, Halla University, Wonju, Gangwon, Republic of Korea;Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA;Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on applications of time-frequency signal processing in wireless communications and bioengineering
Year:
2010

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Abstract

We consider the reconstruction of signals from nonuniformly spaced samples using a projection onto convex sets (POCSs) implemented with the evolutionary time-frequency transform. Signals of practical interest have finite time support and are nearly band-limited, and as such can be better represented by Slepian functions than by sinc functions. The evolutionary spectral theory provides a time-frequency representation of nonstationary signals, and for deterministic signals the kernel of the evolutionary representation can be derived from a Slepian projection of the signal. The representation of low pass and band pass signals is thus efficiently done by means of the Slepian functions. Assuming the given nonuniformly spaced samples are from a signal satisfying the finite time support and the essential band-limitedness conditions with a known center frequency, imposing time and frequency limitations in the evolutionary transformation permit us to reconstruct the signal iteratively. Restricting the signal to a known finite time and frequency support, a closed convex set, the projection generated by the time-frequency transformation converges into a close approximation to the original signal. Simulation results illustrate the evolutionary Slepian-based transform in the representation and reconstruction of signals from irregularly-spaced and contiguous lost samples.