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Information Technology Journal
  Year: 2010 | Volume: 9 | Issue: 6 | Page No.: 1231-1235
DOI: 10.3923/itj.2010.1231.1235
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Sampling Theory: From Shannon Sampling Theorem to Compressing Sampling

Wu Guochang, Zhang Yadong and Yang Xiaohui

It is known that sampling theory lies at the heart of signal processing devices and communication systems. This study presents an account of the current state of sampling theorem after Shannon’s formulation of the sampling theorem. Our emphasis is on some new tends of sampling theory in recent decade. At first, the problem of vector sampling expansion is argued. Secondly, signal reconstruction from local averages is showed. Thirdly, the issue of sampling theorem in the wavelet subspaces is investigated and some results are given. At last, compressed sampling and its two principles are reviewed.
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  •    Reproducing Systems Generated by Finite Functions
  •    Iterative Weighted Gradient Projection for Sparse Reconstruction
  •    The Cardinal Orthogonal Scaling Function in Higher Dimension
How to cite this article:

Wu Guochang, Zhang Yadong and Yang Xiaohui, 2010. Sampling Theory: From Shannon Sampling Theorem to Compressing Sampling. Information Technology Journal, 9: 1231-1235.

DOI: 10.3923/itj.2010.1231.1235






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