• Microelectronics
  • Vol. 52, Issue 2, 191 (2022)
LI Jiashen1, LI Long1, DENG Honghui1、2, CHEN Hongmei1, MENG Xu1, and YIN Yongsheng1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.13911/j.cnki.1004-3365.zjea019 Cite this Article
    LI Jiashen, LI Long, DENG Honghui, CHEN Hongmei, MENG Xu, YIN Yongsheng. Review of Digital Calibration Techniques Based on Neural Network[J]. Microelectronics, 2022, 52(2): 191 Copy Citation Text show less


    With the development of integrated circuit process, the sizes of transistors are reducing, and the ADCs become faster with lower power consumption. On the other hand, smaller size brings more mismatch error, which will affect the accuracy, so it is necessary to introduce error calibration. In this paper, firstly, the typical error sources and traditional calibration methods of ADC were analyzed. Secondly, basic principle of neural network was given together with the most popular researches for ADC calibration based on neural network, and the advantages and disadvantages of different methods were analyzed. Finally, a system level simulation based on neural network was proposed to calibrate a 14-bit pipelined ADC. The results showed that ENOB was improved from 10 bit to 125 bit, and SFDR was improved from 80 dB to 100 dB.