Abstract
Sampling theory is one of the most powerful results in signal analysis. The objective of sampling is to reconstruct a signal from its samples. Walter extended the Shannon sampling theorem to wavelet subspaces. In this paper we give a further characterization on some shift-invariant subspaces, especially the closed subspaces on which the sampling theorem holds. For some shift-invariant subspaces with sampling property, the sampling functions are explicitly given.
This work was supported by the National Natural Science Foundation of China (Grant No. 60572113).
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Li, X., Yang, D. (2007). A Further Characterization on the Sampling Theorem for Wavelet Subspaces. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2007. ICCS 2007. Lecture Notes in Computer Science, vol 4488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72586-2_144
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DOI: https://doi.org/10.1007/978-3-540-72586-2_144
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