• DocumentCode
    1187850
  • Title

    Bias of mean value and mean square value measurements based on quantized data

  • Author

    Kollár, István

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., CA, USA
  • Volume
    43
  • Issue
    5
  • fYear
    1994
  • fDate
    10/1/1994 12:00:00 AM
  • Firstpage
    733
  • Lastpage
    739
  • Abstract
    This paper investigates the imperfect fulfilment of the validity conditions of the noise model quantization. The general expressions of the deviations of the moments from Sheppard´s corrections are derived. Approximate upper and lower bounds of the bias are given for the measurement of first- and second-order moments of sinusoidal, uniformly distributed, and Gaussian signals. It is shown that because of the uncontrollable mean value at the input of the ADC (offset, drift), the worst-case values have to be investigated; it is illustrated how a simple-form envelope function of the errors can be used as an upper bound. Since the worst-case relative positions of the signal and the quantization characteristics are taken into account, the results are valid for both midtread and midrise quantizers, while in the literature results are given for a selected quantizer type only
  • Keywords
    analogue-digital conversion; error analysis; measurement theory; random noise; ADC; Gaussian signals; Sheppard´s corrections; first-order moments; lower bounds; mean square value measurements; mean value; midrise quantizers; midtread quantizers; noise model quantization; quantization characteristics; quantized data; second-order moments; selected quantizer; simple-form envelope function; sine wave; uncontrollable mean value; upper bounds; worst-case relative positions; worst-case values; Additive noise; Convolution; Genetic expression; Instruments; Noise measurement; Probability density function; Quantization; Random variables; Read only memory; Upper bound;
  • fLanguage
    English
  • Journal_Title
    Instrumentation and Measurement, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9456
  • Type

    jour

  • DOI
    10.1109/19.328894
  • Filename
    328894