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Challenges and Opportunities of Artificial Intelligence for Electronic Design: Theory...
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Challenges and Opportunities of Artificial Intelligence for Electronic Design: Theory and Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 27527

Special Issue Editor

Prof. Dr. Antonio Orlandi

E-Mail Website
Guest Editor
Department of Industrial and Information Engineering and Economics, University of L'Aquila, via G. Gronchi, 18, I-67100 L’Aquila, Italy
Interests: signal and power Integrity; electromagnetic compatibility; artificial intelligence; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Researchers in computer science and statistics have developed advanced techniques to obtain insights from large disparate datasets. Data may be of different types, from different sources, and of different qualities (structured and unstructured data). These techniques can leverage the ability of computers to perform tasks, such as recognizing images and processing natural languages, by learning from experience. The application of computational tools to address tasks traditionally requiring human sophistication is broadly termed ‘artificial intelligence’ (AI). As a field, AI has existed for many years. However, recent increases in computing power coupled with increases in the availability and quantity of data have resulted in a resurgence of interest in potential applications of artificial intelligence. These applications are already being used in several fields of engineering; they are increasingly being used in the electronic hardware design as well.

This Special Issue aims to provide readers with a timely snapshot of the state-of-the-art developments in the field of artificial intelligence applied to the modeling, design, validation, and testing of electronic hardware. The topics span from the theory, the algorithms, and the neural network architectures to improve the accuracy, efficiency, and optimization of AI processes to practical applications, innovative tools, and prototypes that help and support the correct and advanced design of electronic systems and components.

Prof. Dr. Antonio Orlandi
Guest Editor

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 submissions that pass pre-check are 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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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

  • artificial intelligence
  • artificial neural networks
  • big data management
  • learning techniques
  • optimization
  • printed circuit boards
  • analog circuits
  • RF systems
  • IC and packages
  • power delivery networks
  • signal integrity
  • power integrity
  • CAD and tools

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Published Papers (5 papers)

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Research

16 pages, 5161 KiB  
Article
Efficient Iterative Process Based on an Improved Genetic Algorithm for Decoupling Capacitor Placement at Board Level
by Francesco de Paulis, Riccardo Cecchetti, Carlo Olivieri, Stefano Piersanti, Antonio Orlandi and Markus Buecker
Electronics 2019, 8(11), 1219; https://doi.org/10.3390/electronics8111219 - 24 Oct 2019
Cited by 8 | Viewed by 3222
Abstract
To reduce the noise created by a power delivery network, the number, the value of decoupling capacitors and their arrangement on the board are critical to reaching this goal. This work deals with specific improvements, implemented on a genetic algorithm, which used for [...] Read more.
To reduce the noise created by a power delivery network, the number, the value of decoupling capacitors and their arrangement on the board are critical to reaching this goal. This work deals with specific improvements, implemented on a genetic algorithm, which used for the optimization of the decoupling capacitors in order to obtain the frequency spectrum of the input impedance in different positions on the network, below previously defined values. Measurements are performed on a specifically manufactured board in order to validate the effectiveness of the proposed algorithm and the optimization results obtained for a specific example board. Full article
(This article belongs to the Special Issue Challenges and Opportunities of Artificial Intelligence for Electronic Design: Theory and Applications)
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18 pages, 3846 KiB  
Article
Low-Cost Multi-Objective Optimization of Multiparameter Antenna Structures Based on the l1 Optimization BPNN Surrogate Model
by Jian Dong, Wenwen Qin and Jinjun Mo
Electronics 2019, 8(8), 839; https://doi.org/10.3390/electronics8080839 - 26 Jul 2019
Cited by 9 | Viewed by 3281
Abstract
The development of modern wireless communication systems not only requires the antenna to be lightweight, low cost, easy to manufacture and easy to integrate but also imposes requirements on the miniaturization, wideband, and multiband design of the antenna. Therefore, designing an antenna that [...] Read more.
The development of modern wireless communication systems not only requires the antenna to be lightweight, low cost, easy to manufacture and easy to integrate but also imposes requirements on the miniaturization, wideband, and multiband design of the antenna. Therefore, designing an antenna that quickly and effectively meets multiple performance requirements is of great significance. To solve the problem of the large computational cost of traditional multi-objective antenna design methods, this paper proposes a backpropagation neural network surrogate model based on l1 optimization (l1-BPNN). The l1 optimization method tends to punish larger weight values and select smaller weight values so as to preserve a small amount of important weights and reset relatively unimportant weights to zero. By using l1 optimization method, the network mapping structure can be automatically adjusted to achieve the most suitable and compact structure of the surrogate model. Furthermore, for multi-parameter antenna design problems, a fast multi-objective optimization framework is constructed using the proposed l1-BPNN as a surrogate model. The framework is illustrated using a miniaturized multiband antenna design case, and a comparison with previously published methods, as well as numerical validation, is also provided. Full article
(This article belongs to the Special Issue Challenges and Opportunities of Artificial Intelligence for Electronic Design: Theory and Applications)
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20 pages, 4555 KiB  
Article
Automatic Emotion-Based Music Classification for Supporting Intelligent IoT Applications
by Yeong-Seok Seo and Jun-Ho Huh
Electronics 2019, 8(2), 164; https://doi.org/10.3390/electronics8020164 - 1 Feb 2019
Cited by 65 | Viewed by 8281
Abstract
With the arrival of the fourth industrial revolution, new technologies that integrate emotional intelligence into existing IoT applications are being studied. Of these technologies, emotional analysis research for providing various music services has received increasing attention in recent years. In this paper, we [...] Read more.
With the arrival of the fourth industrial revolution, new technologies that integrate emotional intelligence into existing IoT applications are being studied. Of these technologies, emotional analysis research for providing various music services has received increasing attention in recent years. In this paper, we propose an emotion-based automatic music classification method to classify music with high accuracy according to the emotional range of people. In particular, when the new (unlearned) songs are added to a music-related IoT application, it is necessary to build mechanisms to classify them automatically based on the emotion of humans. This point is one of the practical issues for developing the applications. A survey for collecting emotional data is conducted based on the emotional model. In addition, music features are derived by discussing with the working group in a small and medium-sized enterprise. Emotion classification is carried out using multiple regression analysis and support vector machine. The experimental results show that the proposed method identifies most of induced emotions felt by music listeners and accordingly classifies music successfully. In addition, comparative analysis is performed with different classification algorithms, such as random forest, deep neural network and K-nearest neighbor, as well as support vector machine. Full article
(This article belongs to the Special Issue Challenges and Opportunities of Artificial Intelligence for Electronic Design: Theory and Applications)
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25 pages, 5858 KiB  
Article
An Optimized Algorithm and Test Bed for Improvement of Efficiency of ESS and Energy Use
by Seung-Mo Je and Jun-Ho Huh
Electronics 2018, 7(12), 388; https://doi.org/10.3390/electronics7120388 - 4 Dec 2018
Cited by 8 | Viewed by 3473
Abstract
The Republic of Korea (ROK) has four distinct seasons. Such an environment provides many benefits, but also brings some major problems when using new and renewable energies. The rainy season or typhoons in summer become the main causes of inconsistent production rates of [...] Read more.
The Republic of Korea (ROK) has four distinct seasons. Such an environment provides many benefits, but also brings some major problems when using new and renewable energies. The rainy season or typhoons in summer become the main causes of inconsistent production rates of these energies, and this would become a fatal weakness in supplying stable power to the industries running continuously, such as the aquaculture industry. This study proposed an improvement plan for the efficiency of Energy Storage System (ESS) and energy use. Use of sodium-ion batteries is suggested to overcome the disadvantages of lithium-ion batteries, which are dominant in the current market; a greedy algorithm and the Floyd–Warshall algorithm were also proposed as a method of scheduling energy use considering the elements that could affect communication output and energy use. Some significant correlations between communication output and energy efficiency have been identified through the OPNET-based simulations. The simulation results showed that the greedy algorithm was more efficient. This algorithm was then implemented with C-language to apply it to the Test Bed developed in the previous study. The results of the Test Bed experiment supported the proposals. Full article
(This article belongs to the Special Issue Challenges and Opportunities of Artificial Intelligence for Electronic Design: Theory and Applications)
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Graphical abstract

23 pages, 15860 KiB  
Article
Customized CAD Modeling and Design of Production Process for One-Person One-Clothing Mass Production System
by Ying Yuan and Jun-Ho Huh
Electronics 2018, 7(11), 270; https://doi.org/10.3390/electronics7110270 - 23 Oct 2018
Cited by 17 | Viewed by 8506
Abstract
Following the development of the Industrial Revolution 4.0, many new types of systems are being designed, introduced, or attempted, even in almost every traditional industry. The clothing industry is no exception. The use of continuously developing production equipment and Information and Communication Technology [...] Read more.
Following the development of the Industrial Revolution 4.0, many new types of systems are being designed, introduced, or attempted, even in almost every traditional industry. The clothing industry is no exception. The use of continuously developing production equipment and Information and Communication Technology (ICT) has a single objective, providing a customized service to all customers. Thus, in this study, the primary research task was to identify ill-balanced aspects or disadvantages of the services previously analyzed to construct a more complete online customized service. This was accomplished by analyzing an automated Computer-Aided Design (CAD) output file containing customer requirements regarding individual clothing items. The secondary research task was to plan and design a clothing manufacturing process to which a one-person one-item mass production system has been applied to achieve a customized service. As a result, for the primary research task, the customers’ requirements for each dress were reflected in attributes, such as color, pattern, or size, and it was possible to obtain an automated CAD output file for each element. Such CAD output files can be used in the production process directly. To find the possibility of upgrading the existing dressmaking process and implement the one-person one-item system, the entire manufacturing process was simulated for the test. Full article
(This article belongs to the Special Issue Challenges and Opportunities of Artificial Intelligence for Electronic Design: Theory and Applications)
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