Special Issue "Applications of Statistics and Machine Learning in Electronics"

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Engineering".

Deadline for manuscript submissions: 25 July 2022.

Special Issue Editors

Prof. Dr. Stefan Hensel
E-Mail Website
Guest Editor
Institute for Machine Learning and Analysis, Department for Electrical Engineering, University of Applied Sciences Offenburg, Offenburg, Germany
Interests: autonomous mobile systems; image processing and machine learning
Prof. Dr. Marin B. Marinov
E-Mail Website
Guest Editor
Faculty of Electronic Engineering and Technology, Technical University of Sofia, Sofia, Bulgaria
Interests: measurement; sensors; actuators; smart sensors; neural networks
Dr. Malinka Ivanova
E-Mail Website
Guest Editor
Faculty of Applied Mathematics and Informatics, Technical University of Sofia, Sofia, Bulgaria
Interests: design and analysis of electronic circuit through machine learning; security and privacy
Dr. Maya Dimitrova
E-Mail Website
Guest Editor
Department of Interactive Robotics and Control Systems, Institute of Robotics, Bulgarian Academy of Sciences, Sofia, Bulgaria
Interests: human-robot interaction; brain-like intelligent agents; pedagogical rehabilitation; socially competent robotic systems
Dr. Hiroaki Wagatsuma
E-Mail Website1 Website2
Guest Editor
Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan
Interests: emergent intelligence; episodic memory and emotion; societal robot; computational neuroscience; neuroinformatics; sport biomechanics; rehabilitation support

Special Issue Information

Dear Colleagues,

It is our great pleasure to invite you to participate in this Special Issue of Computation, named “Applications of Statistics and Machine Learning in Electronics”. It is devoted to better understanding the role of statistics and machine learning in supporting and facilitating a wide variety of engineering tasks in electronics. The Special Issue will publish extended variants of the accepted papers presented at the International Conference on Statistics and Machine Learning in Electronics, but colleagues from all over the world who cannot be a part of the conference are also invited. These papers will follow a rigorous peer-review process to satisfy a high standard of publication.

Statistical methods are utilized in different areas of electronics to model, analyse, and evaluate events, processes, and phenomena. Complex interactions between electronic components, as well as the influence of external or accidental internal factors, can impair the performance of an electronic circuit or device, cause unexpected behaviour and output response, or lead to irreversible damage. Statistical analysis allows malfunctioning components and devices to be thoroughly investigated and corrected. In addition, statistical methods are applied to assess the quality of the manufacturing process, ensuring the production of electronic components and devices that possess characteristics according to technical specifications.

The applications of machine and deep learning in electronics contribute to the study, prediction, and better understanding of the behaviour of electronic circuits and devices. Machine learning algorithms and artificial neural networks can model electronic circuits and solve complex problems. They are also applied in the field of measurement, testing, and diagnostics. Methodologies and models for processing "big data" and building forecasting and analytical models to support decision making and solve engineering problems could be created to implement intelligent electronic systems.

Fuzzy logic implementation in control systems and systems, regulating one or several variables, is also in the scope of the discussion.

The topics of the Special Issue include but are not limited to the following research fields: statistics; machine and deep learning; and fuzzy logic methods, algorithms, techniques, methodologies, and models in:

  • Electronic circuit design;
  • Electronic circuit analysis;
  • Electronic circuit and device testing and diagnosis;
  • Electronics circuit and device measurement;
  • Manufacturing of electronic components and devices;
  • Electronic process management;
  • Quality management in electronics;
  • Digital twins.

Prof. Dr. Stefan Hensel
Prof. Dr. Marin B. Marinov
Dr. Malinka Ivanova
Dr. Maya Dimitrova
Dr. Hiroaki Wagatsuma
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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 single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning
  • artificial neural networks
  • electronics
  • intelligent systems
  • manufacturing process
  • measurement and control
  • smart sensors
  • testing and diagnosis

Published Papers

This special issue is now open for submission.
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