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10: Sampling and Reconstruction

  • Page ID
    22906
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    • 10.1: Signal Sampling
      This module introduces sampling of a continuous time signal to produce a discrete time signal, including a computation of the spectrum of the sampled signal and a discussion of its implications for reconstruction.
    • 10.2: Sampling Theorem
      This module builds on the intuition developed in the sampling module to discuss the Nyquist-Shannon sampling theorem, including a full statement and a proof.
    • 10.3: Signal Reconstruction
      This module describes the reconstruction, also known as interpolation, of a continuous time signal from a discrete time signal, including a discussion of cardinal spline filters.
    • 10.4: Perfect Reconstruction
      This module examines the conditions and filters involved in perfect reconstruction.
    • 10.5: Aliasing Phenomena
      This module introduces aliasing phenomena and discusses its implications for reconstruction.
    • 10.6: Anti-Aliasing Filters
      This module discusses the use of anti-aliasing filters when sampling at a rate below the Nyquist frequency.
    • 10.7: Discrete Time Processing of Continuous Time Signals
      This module discusses the theory and practical considerations behind the use of discrete time tools to process of continuous time signals.


    This page titled 10: Sampling and Reconstruction is shared under a CC BY license and was authored, remixed, and/or curated by Richard Baraniuk et al..

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