An Accurate and Fast Method for Improving ADC Nonlinearity

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Mohammed Abdulmahdi Mohammedali, Qais Al-Gayem
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引用次数: 0

Abstract

Errors in analog-to-digital conversion (ADC) occur due to internal links or other electronic parts; faults that may occur during code conversion cannot be overlooked because signal digitalisation demands a large dynamic range and high resolution. This paper presents a new and accurate self-test method to compensate for one of the most effective errors of ADC because of its effect, which may result in a missing code, which is a differential nonlinear (DNL) of a 10-bit SAR-ADC. The proposed method includes three stages: DNL error modelling for nonideal system implementation, detection, and correction. To evaluate the proposed technique, sinusoidal and sawtooth signals are applied as analog inputs to the proposed system. Adaptivity, speed, and accuracy are the main motivations of this work, which provide high accuracy compared to other techniques, up to 9.6 ENOB and 59.2 SNR with sawtooth signal and 9.5 ENOB and 59.2 SNR with sinewave signals.
一种精确、快速改善ADC非线性的方法
模数转换(ADC)由于内部链接或其他电子部件而发生错误;由于信号数字化要求大动态范围和高分辨率,码转换过程中可能出现的故障不容忽视。本文提出了一种新的、精确的自测试方法来补偿ADC由于其影响而产生的最有效误差之一,即10位SAR-ADC的微分非线性(DNL)缺失码。该方法包括三个阶段:非理想系统实现的DNL误差建模、检测和校正。为了评估所提出的技术,正弦和锯齿信号作为模拟输入应用于所提出的系统。自适应、速度和精度是这项工作的主要动机,与其他技术相比,它提供了很高的精度,锯齿波信号高达9.6 ENOB和59.2信噪比,正弦波信号高达9.5 ENOB和59.2信噪比。
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来源期刊
Applied Computational Intelligence and Soft Computing
Applied Computational Intelligence and Soft Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
6.10
自引率
3.40%
发文量
59
审稿时长
21 weeks
期刊介绍: Applied Computational Intelligence and Soft Computing will focus on the disciplines of computer science, engineering, and mathematics. The scope of the journal includes developing applications related to all aspects of natural and social sciences by employing the technologies of computational intelligence and soft computing. The new applications of using computational intelligence and soft computing are still in development. Although computational intelligence and soft computing are established fields, the new applications of using computational intelligence and soft computing can be regarded as an emerging field, which is the focus of this journal.
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