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An extension of Kramer’s sampling theorem for not necessarily “bandlimited” signals – the aliasing error. (English) Zbl 0835.94004

Summary: Kramer’s sampling theorem, a generalization of Shannon’s sampling theorem, states that a function \(f\) which is representable as a finite integral transform can be reconstructed from sample values \(f(t_k)\) in terms of a series expansion with respect to a complete orthogonal set. The aim of this paper is to investigate the error occurring when this expansion is used for a function \(f\) which is representable as an infinite rather than as a finite integral transform. In particular, it is shown that in many applications this error tends to zero when the distance between the sampling points \(t_k\) tends to zero.

MSC:

94A12 Signal theory (characterization, reconstruction, filtering, etc.)
41A25 Rate of convergence, degree of approximation
41A58 Series expansions (e.g., Taylor, Lidstone series, but not Fourier series)
34B24 Sturm-Liouville theory
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