Embedded and Integrated Circuits and Systems in Real Engineering Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 18611

Special Issue Editors


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Guest Editor
Department of Electronics, Instituto Nacional de Astrofísica, Optica y Electrónica (INAOE), Tonantinztla, Puebla 72840, Mexico
Interests: analog signal processing; integrated circuits; optimization by meta-heuristics; fractional-order chaotic systems; security in internet of things; analog/RF and mixed-signal design automation tools
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Engineering, Architecture and Design, Universidad Autónoma de Baja California, Ensenada 22860, Baja California, México
Interests: internet of things; cyber security; machine learning; artificial intelligence; embedded systems

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Guest Editor
School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA
Interests: mixed-signal integrated circuits; embedded systems; wireless sensors energy harvesting; optical communications and image sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Embedded systems, such as field-programmable gate arrays (FPGA), field-programmable analog arrays (FPAA), Raspberry Pi, and microcontrollers, have demonstrated their usefulness in the development of applications in a wide variety of engineering topics, including software-defined radio, digital filters, neuromorphic networks, secure communications, control and synchronization, image processing, and so on. Some of these applications are required in the internet of things (IoT) and artificial intelligence for IoT, so designing integrated circuits faces the challenge of providing very low voltage and low power consumption for wireless systems. This Special Issue welcomes work related to the design of circuits and systems for signal-processing applications.

Potential topics include, but are not limited to, the following:

  • Devices, circuits, and systems designed with modern integrated circuit technologies;
  • Theory on devices, circuits, and systems for modern applications;
  • Modeling, simulation, and optimization of circuits and systems;
  • Embedded/hybrid hardware for IoT and neuromorphic systems;
  • Speech/video signal-processing circuits and systems;
  • Artificial intelligence in circuits and systems for engineering applications;
  • Integrated circuits and systems for biomedical and industrial applications.

Prof. Dr. Esteban Tlelo-Cuautle
Dr. Everardo Inzunza-González
Dr. Walter Leon-Salas
Guest Editors

Manuscript Submission Information

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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

  • integrated circuits
  • embedded hardware
  • internet of things
  • circuits and systems
  • artificial intelligence
  • engineering applications

Published Papers (8 papers)

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Research

15 pages, 5537 KiB  
Article
7T Magnetic Compatible Multimodality Electrophysiological Signal Recording System
by Jiadong Pan, Jie Xia, Fan Zhang, Luxi Zhang, Shaomin Zhang, Gang Pan and Shurong Dong
Electronics 2023, 12(17), 3648; https://doi.org/10.3390/electronics12173648 - 29 Aug 2023
Cited by 1 | Viewed by 1258
Abstract
This paper developed a comprehensive magnetic resonance imaging (MRI)-compatible electrophysiological (EP) acquisition system, which can acquire various physiological electrical signals, including electrocardiography (ECG), electromyography (EMG), electroencephalography (EEG) and electrocorticogram (ECoG), and EP recording combined with multimodal stimulation. The system is designed to be [...] Read more.
This paper developed a comprehensive magnetic resonance imaging (MRI)-compatible electrophysiological (EP) acquisition system, which can acquire various physiological electrical signals, including electrocardiography (ECG), electromyography (EMG), electroencephalography (EEG) and electrocorticogram (ECoG), and EP recording combined with multimodal stimulation. The system is designed to be compatible with the 7-Tesla (7T) ultra-high field MRI environment, providing convenience for neuroscience and physiological research. To achieve MRI compatibility, the device uses magnetically compatible materials and shielding measures on the hardware and algorithm processing on the software side. Different filtering algorithms are adopted for different signals to suppress all kinds of interference in the MRI environment. The system can allow input signals up to ±0.225 V and channels up to 256. The equipment has been tested and proven to be able to collect a variety of physiological electrical signals effectively. When scanned under the condition of a 7T high-intensity magnetic field, the system does not generate obvious heating and can meet the safety requirements of MRI and EEG acquisition requirements. Moreover, an algorithm is designed and improved to efficiently and automatically remove the gradient artifact (GA) noise generated by MRI, which is a thousand-fold gradient artifact. Overall, this work proposes a complete, portable, MRI-compatible system that can collect a variety of physiological electrical signals and integrate more efficient GA removal algorithms. Full article
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18 pages, 5577 KiB  
Article
FPGA-Based Chaotic Image Encryption Using Systolic Arrays
by Furkan Ciylan, Bünyamin Ciylan and Mehmet Atak
Electronics 2023, 12(12), 2729; https://doi.org/10.3390/electronics12122729 - 19 Jun 2023
Cited by 3 | Viewed by 1371
Abstract
Along with the recent advancements in video streaming, concerns over the security of transferred data have increased. Thus, the development of fast and reliable image encryption methodologies has become an emerging research area in the field of communications. In this paper, a systolic [...] Read more.
Along with the recent advancements in video streaming, concerns over the security of transferred data have increased. Thus, the development of fast and reliable image encryption methodologies has become an emerging research area in the field of communications. In this paper, a systolic array-based image encryption architecture is proposed. Systolic arrays are used to apply the convolution operation, and a Lü–Chen chaotic oscillator is used to obtain a convolutional filter. To decrease resource consumption, a method to fuse confusion and diffusion processes by using systolic arrays is also proposed in this paper. The results show that the proposed method is highly secure against some differential and statistical attacks. It is also shown that the proposed method has a high speed of encryption compared to other methods. Full article
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14 pages, 5825 KiB  
Communication
A 1 + α Order Generalized Butterworth Filter Structure and Its Field Programmable Analog Array Implementation
by Julia Nako, Costas Psychalinos and Ahmed S. Elwakil
Electronics 2023, 12(5), 1225; https://doi.org/10.3390/electronics12051225 - 3 Mar 2023
Cited by 9 | Viewed by 1992
Abstract
Fractional-order Butterworth filters of order 1 + α (0 < α < 1) can be implemented by a unified structure, using the method presented in this paper. The main offered benefit is that the cutoff frequencies of the filters are fully controllable using [...] Read more.
Fractional-order Butterworth filters of order 1 + α (0 < α < 1) can be implemented by a unified structure, using the method presented in this paper. The main offered benefit is that the cutoff frequencies of the filters are fully controllable using a very simple method and, also, various types of filters (e.g., low-pass, high-pass, band-pass, and band-stop) could be realized. Thanks to the employment of a Field Programmable Analog Array device, the implementation of the introduced method is fully reconfigurable, in the sense that various types of filter functions as well as their order are both programmable. Full article
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15 pages, 1145 KiB  
Article
Multi-Stage Ensemble-Based System for Glaucomatous Optic Neuropathy Diagnosis in Fundus Images
by Carlos A. Vásquez-Rochín, Miguel E. Martínez-Rosas, Humberto Cervantes de Ávila, Gerardo Romo-Cárdenas, Priscy A. Luque-Morales and Manuel M. Miranda-Velasco
Electronics 2023, 12(4), 1046; https://doi.org/10.3390/electronics12041046 - 20 Feb 2023
Cited by 1 | Viewed by 1280
Abstract
Recent developments in Computer-aided Diagnosis (CAD) systems as a countermeasure to the increasing number of untreated cases of eye diseases related to visual impairment (such as diabetic retinopathy or age-related macular degeneration) have the potential to yield in low-to-mid income countries a comfortable [...] Read more.
Recent developments in Computer-aided Diagnosis (CAD) systems as a countermeasure to the increasing number of untreated cases of eye diseases related to visual impairment (such as diabetic retinopathy or age-related macular degeneration) have the potential to yield in low-to-mid income countries a comfortable and accessible alternative to obtaining a general ophthalmological study necessary for follow-up medical attention. In this work, a multi-stage ensemble-based system for the diagnosis of glaucomatous optic neuropathy (GON) is proposed. GON diagnosis is based on a binary classification procedure working in conjunction with a multi-stage block based on image preprocessing and feature extraction. Our preliminary data show similar results compared to current studies considering metrics such as Accuracy, Sensitivity, Specificity, AUC (AUROC), F1score, and the use of Matthews Correlation Coefficient (MCC) as an additional performance metric is proposed. Full article
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22 pages, 13915 KiB  
Article
Classifying Brain Tumors on Magnetic Resonance Imaging by Using Convolutional Neural Networks
by Marco Antonio Gómez-Guzmán, Laura Jiménez-Beristaín, Enrique Efren García-Guerrero, Oscar Roberto López-Bonilla, Ulises Jesús Tamayo-Perez, José Jaime Esqueda-Elizondo, Kenia Palomino-Vizcaino and Everardo Inzunza-González
Electronics 2023, 12(4), 955; https://doi.org/10.3390/electronics12040955 - 14 Feb 2023
Cited by 44 | Viewed by 6814
Abstract
The study of neuroimaging is a very important tool in the diagnosis of central nervous system tumors. This paper presents the evaluation of seven deep convolutional neural network (CNN) models for the task of brain tumor classification. A generic CNN model is implemented [...] Read more.
The study of neuroimaging is a very important tool in the diagnosis of central nervous system tumors. This paper presents the evaluation of seven deep convolutional neural network (CNN) models for the task of brain tumor classification. A generic CNN model is implemented and six pre-trained CNN models are studied. For this proposal, the dataset utilized in this paper is Msoud, which includes Fighshare, SARTAJ, and Br35H datasets, containing 7023 MRI images. The magnetic resonance imaging (MRI) in the dataset belongs to four classes, three brain tumors, including Glioma, Meningioma, and Pituitary, and one class of healthy brains. The models are trained with input MRI images with several preprocessing strategies applied in this paper. The CNN models evaluated are Generic CNN, ResNet50, InceptionV3, InceptionResNetV2, Xception, MobileNetV2, and EfficientNetB0. In the comparison of all CNN models, including a generic CNN and six pre-trained models, the best CNN model for this dataset was InceptionV3, which obtained an average Accuracy of 97.12%. The development of these techniques could help clinicians specializing in the early detection of brain tumors. Full article
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13 pages, 5396 KiB  
Article
FPGA Implementation of a Chaotic Map with No Fixed Point
by Claudio García-Grimaldo, Ciro Fabián Bermudez-Marquez, Esteban Tlelo-Cuautle and Eric Campos-Cantón
Electronics 2023, 12(2), 444; https://doi.org/10.3390/electronics12020444 - 14 Jan 2023
Cited by 13 | Viewed by 1885
Abstract
The employment of chaotic maps in a variety of applications such as cryptosecurity, image encryption schemes, communication schemes, and secure communication has been made possible thanks to their properties of high levels of complexity, ergodicity, and high sensitivity to the initial conditions, mainly. [...] Read more.
The employment of chaotic maps in a variety of applications such as cryptosecurity, image encryption schemes, communication schemes, and secure communication has been made possible thanks to their properties of high levels of complexity, ergodicity, and high sensitivity to the initial conditions, mainly. Of considerable interest is the implementation of these dynamical systems in electronic devices such as field programmable gate arrays (FPGAs) with the intention of experimentally reproducing their dynamics, leading to exploiting their chaotic properties in real phenomena. In this work, the implementation of a one-dimensional chaotic map that has no fixed points is performed on an FPGA device with the objective of being able to reproduce its chaotic behavior as well as possible. The chaotic behavior of the introduced system is determined by estimating the Lyapunov exponents and its chaotic behavior is also analyzed using bifurcation diagrams. Simulations of the system are realized via Matlab, as well as in C and the very high-speed integrated circuit (VHSIC) hardware description language (VHDL). Experimental results on FPGA show that they are like those obtained in the simulations; therefore, this chaotic dynamical system could be used as an element in some encryption schemes such as in the generation of cryptographically secure pseudorandom numbers. Full article
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11 pages, 2069 KiB  
Article
Generating Even More Chaotic Instances in Hardware
by Luis Gerardo de la Fraga and Brisbane Ovilla-Martínez
Electronics 2023, 12(2), 332; https://doi.org/10.3390/electronics12020332 - 8 Jan 2023
Cited by 1 | Viewed by 1230
Abstract
It is well known that multiplication inside a computer does not follow the associative property because of roundoff effects. It is possible to use this fact to generate other different chaotic instances of chaotic maps or oscillators when a multiplication of three terms [...] Read more.
It is well known that multiplication inside a computer does not follow the associative property because of roundoff effects. It is possible to use this fact to generate other different chaotic instances of chaotic maps or oscillators when a multiplication of three terms appears. Chaos is very sensitive to small changes in the initial conditions and amplifies these small rounding effects. We use this condition to build different chaotic instances, which give different results, of the Lü oscillator and the 2D map, and we show one application to create new instances of a pseudo random number generator using the 2D map. Both chaotic systems are simulated in software and in hardware within an FPGA where another 144 different 2D map instances and 81 different Lü oscillators can be created. To best of our knowledge, it is the first paper that analyze the construction of new chaotic entities by using the roundoff effects. Full article
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13 pages, 2773 KiB  
Article
Deterministic Brownian-like Motion: Electronic Approach
by José Luis Echenausía-Monroy, Eric Campos, Rider Jaimes-Reátegui, Juan Hugo García-López and Guillermo Huerta-Cuellar
Electronics 2022, 11(18), 2949; https://doi.org/10.3390/electronics11182949 - 17 Sep 2022
Cited by 6 | Viewed by 1590
Abstract
Brownian motion is a dynamic behavior with random changes over time (stochastic) that occurs in many vital functions related to fluid environments, stock behavior, or even renewable energy generation. In this paper, we present a circuit implementation that reproduces Brownian motion based on [...] Read more.
Brownian motion is a dynamic behavior with random changes over time (stochastic) that occurs in many vital functions related to fluid environments, stock behavior, or even renewable energy generation. In this paper, we present a circuit implementation that reproduces Brownian motion based on a fully deterministic set of differential equations. The dynamics of the electronic circuit are characterized using four well-known metrics of Brownian motion, namely: (i) Detrended Fluctuation Analysis (DFA), (ii) power law in the power spectrum, (iii) normal probability distribution, and (iv) Mean Square Displacement (MSD); where traditional Brownian motion exhibits linear time growth of the MSD, a Gaussian distribution, a 2 power law of the frequency spectrum, and DFA values close to 1.5. The obtained results show that for a certain combination of values in the deterministic model, the dynamics in the electronic circuit are consistent with the expectations for a stochastic Brownian behavior. The presented electronic circuit improves the study of Brownian behavior by eliminating the stochastic component, allowing reproducibility of the results through fully deterministic equations, and enabling the generation of physical signals (analog electronic signals) with Brownian-like properties with potential applications in fields such as medicine, economics, genetics, and communications, to name a few. Full article
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