You, Hao, Amirsoleimani, Amirali, Xu, Jianxiong, Rahimi Azghadi, Mostafa, and Genov, Roman (2023) A subranging nonuniform sampling memristive neural network-based analog-to-digital converter. Memories - Materials, Devices, Circuits and Systems, 4. 100038.

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Abstract

This work presents a novel 4-bit subranging nonuniform sampling (NUS) memristive neural network-based analog-to-digital converter (ADC) with improved performance trade-off among speed, power, area, and accuracy. The proposed design preserves the memristive neural network calibration and utilizes a trainable memristor weight to adapt to device mismatch and increase accuracy. Rather than conventional binary searching, we adopt quaternary searching in the ADC to realize subranging architecture’s coarse and fine bits determination. A level-crossing nonuniform sampling (NUS) is introduced to the proposed ADC to enhance the ENOB under the same resolutions, power, and area consumption. Area and power consumption are reduced through circuit sharing between different stages of bit determination. The proposed 4-bit ADC achieves a highest ENOB of 5.96 and 5.6 at cut-off frequency (128 ) with power consumption of 0.515 and a figure of merit (FoM) of 82.95.

Item ID:	81673
Item Type:	Article (Research - C1)
ISSN:	2773-0646
Copyright Information:	© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
Date Deposited:	23 Jan 2024 23:51
FoR Codes:	40 ENGINEERING > 4009 Electronics, sensors and digital hardware > 400901 Analog electronics and interfaces @ 100%
SEO Codes:	22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220404 Computer systems @ 100%
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