NDLI: Effect of Inter-Sample Spacing Constraint on Spectrum Estimation with Irregular Sampling

Content Provider	IEEE Xplore Digital Library
Author	Srivastava, R. Sengupta, D.
Copyright Year	1963
Abstract	A practical constraint that comes in the way of spectrum estimation of a continuous time stationary stochastic process is the minimum separation between successively observed samples of the process. When the underlying process is not band-limited, sampling at any uniform rate leads to aliasing, while certain stochastic sampling schemes, including Poisson process sampling, are rendered infeasible by the constraint of minimum separation. It is shown in this paper that, subject to this constraint, no point process sampling scheme is alias-free for the class of all spectra. It turns out that point process sampling under this constraint can be alias-free for band-limited spectra. However, the usual construction of a consistent spectrum estimator does not work in such a case. Simulations indicate that a commonly used estimator, which is consistent in the absence of this constraint, performs poorly when the constraint is present. These results should help practitioners in rationalizing their expectations from point process sampling as far as spectrum estimation is concerned, and motivate researchers to look for appropriate estimators of bandlimited spectra.
Sponsorship	IEEE Information Theory Society
Starting Page	4709
Ending Page	4719
Page Count	11
File Size	302319
File Format	PDF
ISSN	00189448
Volume Number	57
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Spectral analysis Nonuniform sampling Estimation Bandwidth Stochastic processes Density measurement Exponential distribution spectral density Aliasing nonuniform sampling renewal processes
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Computer Science Applications

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