Behavior-level Analysis of a Successive Stochastic Approximation Analog-to-Digital Conversion System for Multi-channel Biomedical Data Acquisition

Tani, Sadahiro; Matsuoka, Toshimasa; Hirai, Yusaku; Kurata, Toshifumi; Tatsumi, Keiji; Asano, Tomohiro; Ueda, Masayuki; Kamata, Takatsugu

doi:https://doi.org/10.1587/transfun.e100.a.2073

Behavior-level Analysis of a Successive Stochastic Approximation Analog-to-Digital Conversion System for Multi-channel Biomedical Data Acquisition

Tani, Sadahiro; Matsuoka, Toshimasa; Hirai, Yusaku et al.

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences, 2017, E100-A(10), 2073-2085

Number of Access:899（2025-08-15 06:46 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/65064

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Title	Behavior-level Analysis of a Successive Stochastic Approximation Analog-to-Digital Conversion System for Multi-channel Biomedical Data Acquisition
Creator	CreatorName Tani, Sadahiro
	NRID 1000080324820 1000080324820 ORCID 0000-0003-3876-2679 0000-0003-3876-2679 researchmap permalink read0068628 read0068628 Scopus Author ID 7402741552 7402741552 CreatorName Matsuoka, Toshimasa
	CreatorName Hirai, Yusaku
	CreatorName Kurata, Toshifumi
	CreatorName Tatsumi, Keiji
	CreatorName Asano, Tomohiro
	CreatorName Ueda, Masayuki
	CreatorName Kamata, Takatsugu
Subject	SAR-ADC
	DAC error calibration
	stochastic A/D conversion
	mismatch
	machine learning
Abstract	In the present paper, we propose a novel high-resolution analog-to-digital converter (ADC) for low-power biomedical analog frontends, which we call the successive stochastic approximation ADC. The proposed ADC uses a stochastic flash ADC (SF-ADC) to realize a digitally controlled variable-threshold comparator in a successive-approximationregister ADC (SAR-ADC), which can correct errors originating from the internal digital-to-analog converter in the SAR-ADC. For the residual error after SAR-ADC operation, which can be smaller than thermal noise, the SF-ADC uses the statistical characteristics of noise to achieve high resolution. The SF-ADC output for the residual signal is combined with the SAR-ADC output to obtain high-precision output data using the supervised machine learning method.
Publisher	電子情報通信学会
Publisher	The Institute of Electronics, Information and Communication Engineers
Source Title	IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Volume (Issue)	E100-A(10)
Page	2073-2085
Date of Issued	2017-10-01
Language	English
Handle URL	https://hdl.handle.net/11094/65064
eISSN	17451337
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.1587/transfun.e100.a.2073
Access Rights	open access
CopyRight	Copyright 🄫 2017 The Institute of Electronics, Information and Communication Engineers
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences. 2017, E100-A(10), p. 2073-2085
DC.title	Behavior-level Analysis of a Successive Stochastic Approximation Analog-to-Digital Conversion System for Multi-channel Biomedical Data Acquisition
DC.creator	Tani, Sadahiro
	Matsuoka, Toshimasa
	Hirai, Yusaku
	Kurata, Toshifumi
	Tatsumi, Keiji
	Asano, Tomohiro
	Ueda, Masayuki
	Kamata, Takatsugu
DC.publisher	電子情報通信学会
DC.publisher	The Institute of Electronics, Information and Communication Engineers
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2017-10-01
DC.identifier	https://doi.org/10.1587/transfun.e100.a.2073
DC.subject	SAR-ADC
	DAC error calibration
	stochastic A/D conversion
	mismatch
	machine learning
DCTERMS.abstract	In the present paper, we propose a novel high-resolution analog-to-digital converter (ADC) for low-power biomedical analog frontends, which we call the successive stochastic approximation ADC. The proposed ADC uses a stochastic flash ADC (SF-ADC) to realize a digitally controlled variable-threshold comparator in a successive-approximationregister ADC (SAR-ADC), which can correct errors originating from the internal digital-to-analog converter in the SAR-ADC. For the residual error after SAR-ADC operation, which can be smaller than thermal noise, the SF-ADC uses the statistical characteristics of noise to achieve high resolution. The SF-ADC output for the residual signal is combined with the SAR-ADC output to obtain high-precision output data using the supervised machine learning method.
DC.rights	Copyright 🄫 2017 The Institute of Electronics, Information and Communication Engineers
DC.format	65064
citation_title	Behavior-level Analysis of a Successive Stochastic Approximation Analog-to-Digital Conversion System for Multi-channel Biomedical Data Acquisition
citation_author	Tani, Sadahiro
	Matsuoka, Toshimasa
	Hirai, Yusaku
	Kurata, Toshifumi
	Tatsumi, Keiji
	Asano, Tomohiro
	Ueda, Masayuki
	Kamata, Takatsugu
citation_publisher	電子情報通信学会
citation_language	English
citation_date	2017-10-01
citation_journal_title	IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
citation_volume	E100-A
citation_issue	10
citation_firstpage	2073
citation_lastpage	2085
citation_doi	https://doi.org/10.1587/transfun.e100.a.2073
citation_public_url	https://hdl.handle.net/11094/65064

Behavior-level Analysis of a Successive Stochastic Approximation Analog-to-Digital Conversion System for Multi-channel Biomedical Data Acquisition

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