Noise-shaped quantization for nonuniform sampling

Adam Mashiach, Ram Zamir

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The Nyquist theorem (for perfect reconstruction of a band-limited signal from its noiseless samples) depends, essentially, only on the average sampling rate. In contrast, reconstruction from imperfect samples strongly depends also on the sampling pattern. Specifically, when the samples are corrupted with independent noise, the reconstruction distortion is generally higher for nonuniform sampling than for uniform sampling at the same average rate - a phenomenon known as 'noise amplification'. We show that this degradation in performance can be avoided if the noise spectrum can be controlled; for any periodic nonuniform sampling pattern, there exists a quantization noise-shaping scheme that mitigates the noise amplification. Moreover, a scheme that combines noise shaping, Wiener filtering and entropy-coded dithered quantization (ECDQ) achieves the rate-distortion function of a (white or colored) Gaussian source, up to the granular loss of the lattice quantizer. This loss tends to zero, for a sequence of good latices, as the lattice dimension tends to infinity.

Original languageEnglish
Title of host publication2013 IEEE International Symposium on Information Theory, ISIT 2013
Number of pages5
StatePublished - 2013
Event2013 IEEE International Symposium on Information Theory, ISIT 2013 - Istanbul, Turkey
Duration: 7 Jul 201312 Jul 2013

Publication series

NameIEEE International Symposium on Information Theory - Proceedings


Conference2013 IEEE International Symposium on Information Theory, ISIT 2013

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics


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