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Noise-Shaping Quantization Methods for Frame-Based and Compressive Sampling Systems

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Part of the Applied and Numerical Harmonic Analysis book series (ANHA)

Abstract

Noise shaping refers to an analog-to-digital conversion methodology in which quantization error is arranged to lie mostly outside the signal spectrum by means of oversampling and feedback. Recently it has been successfully applied to more general redundant linear sampling and reconstruction systems associated with frames as well as non-linear systems associated with compressive sampling. This chapter reviews some of the recent progress in this subject.

Keywords

  • Reconstruction Error
  • Sparse Signal
  • Dual Frame
  • Compressive Sampling
  • Compressible Signal

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Acknowledgements

FK and RS acknowledge support by the German Science Foundation (DFG) in the context of the Emmy-Noether Junior Research Group KR 4512/1-1 “RaSenQuaSI”. ÖY was funded in part by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant (22R82411), an NSERC Accelerator Award (22R68054) and an NSERC Collaborative Research and Development Grant DNOISE II (22R07504).

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Chou, E., Güntürk, C.S., Krahmer, F., Saab, R., Yılmaz, Ö. (2015). Noise-Shaping Quantization Methods for Frame-Based and Compressive Sampling Systems. In: Pfander, G. (eds) Sampling Theory, a Renaissance. Applied and Numerical Harmonic Analysis. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-19749-4_4

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