Advances and Applications in Blockchain Technology

A special issue of Electronics (ISSN 2079-9292).

Deadline for manuscript submissions: 15 July 2026 | Viewed by 740

Special Issue Editors


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Guest Editor
SenticNet Team, Nanyang Technological University, Singapore 639798, Singapore
Interests: multimodal AI; wireless sensing; robotics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Communication and Information Engineering, Shanghai University, Shanghai 200444,China
Interests: internet of things; intelligent information processing; pattern recognition
Computer Science, Macquarie University, Sydney, NSW 2113, Australia
Interests: multimodal data processing; blockchain analytics; multimodal emotion and sentiment analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid evolution of electronic systems—ranging from smart sensors and autonomous robots to blockchain-enabled platforms and large-scale multimedia services—is driving an explosion of heterogeneous data. Modern applications must jointly process visual, audio, textual, RF, inertial, transactional, and other streams to achieve reliable perception, secure interaction, and efficient decision-making at scale. This creates an urgent need for multimodal data processing methods that can bridge the gap between low-level electronic signals and high-level intelligent behavior.

This Special Issue aims to bring together cutting-edge research on multimodal learning and sensing for electronic and cyber–physical systems. We welcome contributions that develop novel algorithms, system architectures, and hardware–software co-designs to fuse and interpret diverse modalities in real-world scenarios. Particular emphasis is placed on applications such as blockchain-based analytics for electronic transactions and IoT data, multimodal emotion and sentiment analysis, robotics SLAM and navigation, remote sensing and medical imaging, and trustworthy, efficient deployment on edge and embedded devices.

Topics of interest include, but are not limited to, the following:

  • Multimodal learning and fusion (vision, audio, text, RF, sensor, transactional data) for electronic and IoT systems.
  • Blockchain-based data management, analytics, and security for multimodal and sensor-rich environments.
  • Multimodal emotion and sentiment analysis for human–computer interaction and intelligent services.
  • Robotics SLAM, LiDAR-vision fusion, and multi-sensor navigation in autonomous systems.
  • Multimodal image and signal processing for remote sensing, medical imaging, and industrial inspection.
  • Wireless/5G/6G and RF sensing with multimodal fusion for human activity and understanding behavior.
  • Trustworthy, robust, and energy-efficient multimodal AI on edge, embedded, and resource-constrained platforms.
  • Applications of multimodal data processing in smart cities, intelligent transportation, healthcare, and blockchain-driven ecosystems.

We look forward to receiving high-quality submissions and advancing the state of the art in multimodal data processing for next-generation electronic systems.

Dr. Xianxun Zhu
Prof. Dr. Rui Wang
Dr. Hui Chen
Guest Editors

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Keywords

  • multimodal data processing
  • blockchain analytics
  • multimodal emotion and sentiment analysis
  • robotics SLAM and navigation
  • wireless/RF and 6G sensing
  • computer vision and image processing
  • edge and embedded AI
  • remote sensing and medical imaging

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Published Papers (1 paper)

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Research

16 pages, 19451 KB  
Article
A 200 MS/s 12-Bit Current-Steering DAC Using Split–Sort–Symmetric Grouping for Microdisplay Drivers
by Yichen Gao, Yingqi Feng, Yibo Su, Haoran Zeng and Zunkai Huang
Electronics 2026, 15(5), 1102; https://doi.org/10.3390/electronics15051102 - 6 Mar 2026
Viewed by 379
Abstract
High-resolution microdisplay driver applications impose stringent requirements on the static linearity and dynamic performance of digital-to-analog converters (DACs). To meet these requirements, this paper presents a 200 MS/s 12-bit current-steering DAC. To reduce mismatches among high-weight current sources, a split–sort–symmetric grouping calibration (SSSGC) [...] Read more.
High-resolution microdisplay driver applications impose stringent requirements on the static linearity and dynamic performance of digital-to-analog converters (DACs). To meet these requirements, this paper presents a 200 MS/s 12-bit current-steering DAC. To reduce mismatches among high-weight current sources, a split–sort–symmetric grouping calibration (SSSGC) scheme is introduced, in which each most-significant-bit (MSB) current source is split into sub-cells and reorganized through sorting and symmetric pairing. This approach improves static linearity without complex current measurement or compensation loops. Additionally, a group-domain dynamic element matching (DEM) technique is employed to randomize current-source selection and suppress harmonic distortion. Designed in a 0.18 μm BCD process, the proposed DAC achieves an integral nonlinearity (INL) of 0.79 LSB, a differential nonlinearity (DNL) of 0.42 LSB, and a spurious-free dynamic range (SFDR) of 74.9 dB at an output signal of 4.05 MHz. Full article
(This article belongs to the Special Issue Advances and Applications in Blockchain Technology)
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