• DocumentCode
    1072420
  • Title

    Symbolic Statistical Analysis of SNR Variation for Delta–Sigma Modulators

  • Author

    Tang, Hua

  • Author_Institution
    Minnesota Duluth Univ., Duluth
  • Volume
    54
  • Issue
    8
  • fYear
    2007
  • Firstpage
    720
  • Lastpage
    724
  • Abstract
    Traditional methods for statistical analysis of delta-sigma modulators are based on Monte Carlo analysis to iteratively change the design parameters and evaluate the histogram of signal-to-noise ratio (SNR). But Monte Carlo analysis is time-consuming, especially when a number of candidate designs need to be considered. In this brief, a systematic symbolic formulation of statistical SNR variation is made so that variations of capacitors are directly translated to SNR variation. In addition, the symbolic formulation is derived from a generic modulator topology, so that the derived symbolic formulation is applicable to any topology that is covered by the generic topology. Experiments have shown the symbolic formulation can provide fast and reasonably accurate estimation of statistical SNR variation, especially for high-order modulators.
  • Keywords
    Monte Carlo methods; delta-sigma modulation; modulators; network topology; Monte Carlo analysis; SNR variation; delta-sigma modulators; generic modulator topology; high-order modulators; signal-to-noise ratio; symbolic statistical analysis; Capacitors; Delta modulation; Monte Carlo methods; Process design; Signal analysis; Signal design; Signal to noise ratio; Statistical analysis; System-level design; Topology; Delta–sigma ($Delta Sigma$ ) modulator; signal-to-noise ratio (SNR); statistical analysis; symbolic analysis; system-level design;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems II: Express Briefs, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1549-7747
  • Type

    jour

  • DOI
    10.1109/TCSII.2007.899458
  • Filename
    4277942