Performance Trade-offs and Evolution of ADC Architectures: From Conventional Designs to AI-Driven Hybrid Converters

Siyu Cheng

doi:10.6911/

Authors

Siyu Cheng Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, 999078, China

DOI:

https://doi.org/10.6911/

Keywords:

Analog-to-Digital Converter, Hybrid Architectures, Artificial Intelligence, Performance Optimization.

Abstract

As the crucial connection between the analog and the digital signal, the analog-to-digital converter (ADC) extremely determine the result of modern electronic systems. It is high performance ADC that essential for advancing emerging technologies, such as wireless communication, medical monitoring and intelligent driving. This article is going to analyze basic principles and key indicators of ADC systematically and respectively, like sampling rate, power consumption and signal-to-noise ratio. It also provides comparative research of four mainstream ADC structures which is called SAR, Flash, Sigma-Delta and Pipeline ADC, evaluating their operating principles and suitable applications. Furthermore, the article investigates hybrid ADC architectures, such as Pipeline-SAR and Flash-SAR ADC, and analyzes modern design trends like dual-channel synchronization through case studies of recent Texas Instruments (TI) products. It is meaningful to mention that future ADC evolution is driving towards innovative materials and architectures, adaptive ability and comprehensive utilization of Artificial Intelligence (AI) three general dimensions. In fact, the combination of advanced nanometer processes, innovative hybrid architectures and AI-based dynamic error correct function are identified as vital ways to achieving higher linearity, lower power consumption and complex environmental auto-adaptation.

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