DocumentCode :
925629
Title :
On the truncation error of the cardinal sampling expansion
Author :
Beutler, Frederick J.
Volume :
22
Issue :
5
fYear :
1976
fDate :
9/1/1976 12:00:00 AM
Firstpage :
568
Lastpage :
573
Abstract :
Modern communication theory and practice are heavily dependent on the representation of continuous parameter signals by linear combinations, involving a denumerable set of random variables. Among the best known and most useful is the cardinal series f_{n} (t) = \\sum ^{+n}_{-n} f(k) frac{\\sin \\pi (t - k)}{ \\pi ( t - k )} for deterministic functions and wide-sense stationary stochastic processes bandlimited to (-\\pi, \\pi) . When, as invariably occurs in applications, samples f(k) are available only over a finite period, the resulting finite approximation is subject to a truncation error. For functions which are L_{1} Fourier transforms supported on [-\\pi + \\delta , + \\pi - \\delta ] , uniform trunction error bounds of the form O(n^{-1}) are known. We prove that analogous O(n^{-1}) bounds remain valid without the guard band \\delta and for Fourier-Stieltjes transforms; we require only a bounded variation condition in the vicinity of the endpoints - \\pi and + \\pi of the basic interval. Our methods depend on a Dirichlet kernel representation for f_{n}(t) and on properties of functions of bounded variation; this contrasts with earlier approaches involving series or complex variable theory. Other integral kernels (such as the Fejer kernel) yield certain weighted truncated cardinal series whose errors can also be bounded. A mean-square trunction error bound is obtained for bandlimited wide-sense stationary stochastic processes. This error estimate requires a guard band, and leads to a uniform O(n^{-2}) bound. The approach again employs the Dirichlet kernel and draws heavily on the arguments applied to deterministic functions.
Keywords :
Band-limited signals; Finite-wordlength effects; Signal sampling/reconstruction; Band pass filters; Filtering theory; Finite wordlength effects; Fourier transforms; Kernel; Random variables; Robustness; Sampling methods; Signal sampling; Stochastic processes;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1976.1055601
Filename :
1055601
Link To Document :
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