A topical collection of Digital Technologies Research and Applications (DTRA) (E-ISSN: 2754-5687).
Deadline for manuscript submissions: 31 December 2024
Collection Editor:
Division of Electronics and Informatics, Gunma University, Kiryu, Gunma 376-8515, Japan
Research Interests: analog/mixed-signal circuit design & test; signal processing algorithms
Kyoto University, Kyoto, 606-8501, Japan
Research Interests: Analog/RF IC design
Tokyo Polytechnic University, Kanagawa 243-0297, Japan
Research Interests: Analog/RF IC design Integrated power electronics
Department of Electronics and Infomatics, Mathematics and Physics, Gunma University, Gunma 371-0044, Japan
Research Interests: Measurement technologies
Faculty of Engineering Department of Electronics Engineering and Computer Science, Fukuoka University, Fukuoka, 814-0180, Japan
Research Interests: LSI test technologies
Topical Collection Information:
Dear Colleagues,
Digital technologies are rapidly becoming prevalent in our society, where computers, smartphones, the Internet, AI, IoT, robotics, biomedical systems, and automotive systems are advancing. Their integrated circuits, as well as their testing and measurement related technologies, play a crucial role in differentiating digital-oriented products from those of other companies and countries. This topical collection solicits review papers (survey papers) in the areas of integrated circuit design and test/measurement related technologies, contributing a renewed perspective in the field of digital technologies and applications.
Prof. Dr. Haruo Kobayashi
Prof. Dr. Kiichi Niitsu
Prof. Dr. Toru Sai
Prof. Dr. Tadashi Ito
Prof. Dr. Kentaroh Katoh
Collection Editors
Keywords:
Manuscript Submission Information:
Please visit the Submissions Guidelines page before submitting a manuscript. Submitted papers should be well formatted and use good English. Manuscripts should be submitted online through the online manuscript submission and editorial system. Additionally, please include a cover letter specifying that the manuscript is intended for the Topical Collection "Integrated Circuit Design and Test/Measurement Related Technologies" when submitting it online. Manuscripts can be submitted until the submission deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the Topical Collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract can be sent to the Editorial Office dtra@ukscip.com for announcement on this website.
The Article Processing Charge (APC) for publication in this open access journal is 300 USD. Authors who are unable to cover this cost or those who are invited to submit papers may be eligible for discounts or waivers.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process.
Title: A survey on digitally assisted A/D converters breaking the limitation of analog effort alone on performance and power
Abstract: With continuous CMOS technology scaling and remarkable progress in AI, digital signal processing presents unlimited capability. To fully utilize the capability, an A/D converter needs to provide high-fidelity digital representation of the input analog signal. Interestingly, the A/D converter itself can benefit from digital signal processing since its raw output is already represented in digital form. Such digitally assisted A/D converters can break the limitation of analog effort alone on performance and power by processing the raw digital output appropriately, which is called digital calibration. The digital calibration can be performed in either foreground or background on various types of A/D converters including Nyquist A/D converters, oversampling A/D converters and time-interleaved A/D converters. This survey paper reviews typical works in the field of digitally assisted A/D converters from the mature adaptive-filter-based methods to the recent machine-learning-based methods. Both merits and issues of these methods are discussed with possible applications. Finally, prospect for the future work is given.