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Vol. 1 No. 1 (2020)

Articles

Effects of Rounding and Truncating Methods of Quantization Error and SQNR for Sine Signal

https://doi.org/10.38094/jastt113

Published 2020-03-12

  • Alaaldin Hasso
    • ,
  • Karwan Jacksi

Alaaldin Hasso
Computer Science Dept., Faculty of Science, University of Zakho, Kurdistan Region of Iraq

Karwan Jacksi
Computer Science Dept., Faculty of Science, University of Zakho, Kurdistan Region of Iraq

Journal of Applied Science and Technology Trends

Abstract

Within the Analog to Digital Conversion (ADC), quantization noise is a duplicate of a Quantization Error (QE) which is introduced by quantization. In signal processing and telecommunication systems, the noise is non-linear and depends on the signal type. During the analog, Sine signal converts to the digital (ADC) process, the two methods are used Rounding and Truncating in-order to eliminate the error produced in the digitization process. The rounding method quantize assigns each sample of sine signal to the nearest quantization level. However, making the Truncating would have assigned each sample of sine signal to the quantization level below it. This paper compares the rounding and truncating methods of QE for sine signal, signal to quantization noise ratio, correlation coefficient, and regression equation of a line for both methods. Then, it calculates the residual sum of squares and compares it to the regression equations of the lines.

Keywords

ADC, SQNR, RSS, Quantization Error, Correlation Coefficient, Regression Equation

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