Modeling the influence of components leakage currents on the accuracy of the recurrent LADCS

: pp. 72 - 78
Lviv Polytechnic National University, Department of Computerized Automation Systems
Lviv Polytechnic National University, Department of Computerized Automation Systems
Lviv Polytechnic National University

This work is dedicated to the investigation of errors in the recurrent logarithmic analog-to-digital converters (LADC). A generalized structural diagram of the recurrent LADC with a variable logarithmic base is provided. The implementation features and operating principles are explained. Models of the recurrent LADCs that account for the influence of component leakage currents in the converter circuits have been developed. The models consider changes in the structure of the recurrent LADCs during the conversion process. To improve the speed of LADCs, analog switches with an operational amplifier have been used, reducing the switch resistance in the ON state. This increased the clock frequency to 500 kHz, but also increased leakage currents. For the developed 8-bit the recurrent LADCs operating with 10 – and 12-bit output code precision, errors from leakage currents do not exceed (0.45 and 1.37) 10-3 % for conversion times not exceeding (28 and 78) µs (14 and 39 conversion cycles). Increasing the resolution of the LADCs and their output code results in an increase in these mentioned errors, but they remain significantly smaller than the corresponding quantization errors. However, with each 2 bits of increased precision, the conversion time of the recurrent LADCs increases by 1,5 times. Therefore, increasing precision by more than 2-4 bits is not practical.

  1. Mychuda Z.R. Logarithmic Analog-to-Digital Converters – ADC of the Future, Prostir, Lviv, Ukraine 2002, pp. 242
  2. Zynoviy Mychuda, Hanna Yelisieieva, Zbigniew Szcześniak. Features of implementation of recurrent logarithmic ADCs // Mizhvidomchyi naukovo-tekhnichnyi zbirnyk «Vymiryuvalna tekhnika i metrologia» / «Measuring Equipment and Metrology», 2022, Volume 83, no.4, pp. 5 – 10,
  3. Patent 113138 Ukraina. Logarithmic Analog-to-Digital Converter / Mychuda L.Z., 2016, Biul. №23
  4. Aigerim Tankimanova, Akshay Kumar Maan, Alex Pappachen James. (2017) Level-shifted neural encoded analog-to-digital converter [conference-paper]/ 24th IEEE International Conference on Electronics, Circuits and Systems (ICECS): 5-8 December 2017, Batumi, Georgia. DOI: 10.1109/icecs.2017.8292026
  5. Patent US007345604B2 USA. Analog to Digital Conversion Using Recurrent Neural Networks / Brian Watson, 2008
  6. O.V. Poliarus. Dynamichna neiromerezheva model pervynnoho peretvoriuvacha / O.V. Poliarus, A.O Podorozhniak, A.O. Koval // ISSN 2079-0031 Vestnyk NTU "KhPY". – 2014. – № 35 (1078) – s. 152 – 160
  7. Jongwoo Lee. A 2.5 mW 80 dB DR 36 dB SNDR 22 MS/s Logarithmic Pipeline ADC/ Jongwoo Lee, Joshua Kang, Sunghyun Park, Jae-sun Seo, Jens Anders, Jorge Guilherme, Michael P. Flynn// IEEE JOURNAL OF SOLID- STATE CIRCUITS, vol.44, 2009, nr.10, pp.2755-2765
  8. M. Santos et al., Logarithmic Voltage-to-Time Converter for Analog-to-Digital Signal Conversion, Lecture Notes in Electrical Engineering, Springer Nature Switzerland AG 2019,
  9. M. Santosa, N. Horta, J. Guilherme, “A survey on nonlinear analog-to-digital converters”, Integration, the VLSI Journal, Vol. 47, Issue 1, pp. 12–22, January 2014
  10. Silar Sirimasakul, Apinunt Thanachayanont. A logarithmic level-crossing ADC. 2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI- CON). 978-1-5386-0449-6/17/$31.00 (c) 2017 IEEE, 576-579
  11. А. Thanachayanont. A 1-V, 330-nW, 6-Bit Current-Mode Logarithmic Cyclic ADC for ISFET-Based pH Digital Readout System. Circuits Syst Signal Process DOI 10.1007/s00034-014-9908-0. 1 October 2014 © Springer Science+Business Media New York 2014
  12. Sundarasaradula Y., Constandinou T.G., Thanachayanont A. A 6-bit two-step successive approximation logarithmic   ADC   for   biomedical   applications.   –   2016.   URL: