Advanced Signal Processing and Circuit Analysis

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

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 9381

Special Issue Editors


E-Mail Website
Guest Editor

E-Mail Website
Guest Editor
College of Engineering, Najran University, Najran 61441, Saudi Arabia
Interests: diagnostics and prognostics; pattern recognition; statistical analysis of big data; machine fault diagnostics; non-destructive testing; condition monitoring; Internet of things; artificial intelligence; industrial electronics; smart cities and smart healthcare
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Electrical and Computer Engineering, University of Texas at El Paso, 500 West University Avenue, El Paso, TX 79968, USA
Interests: biomedical engineering; mechatronics systems engineering; robotics and automation; electrical measurements of non-electrical quantities; machine vision and pattern recognition; applications of soft computing; sensors (validation, fusion)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The purpose of this Special Issue is to publish high-quality research in advanced signal processing and electric circuit analysis. The electronic circuit consists of vital components such as diodes, resistors, inductors, capacitors, transformers, amplifiers and batteries. Various types of sensors are employed in circuits to measure quantities such as voltage, current, flux and acceleration, etc. The signals coming from sensors need signal conditioning and processing networks to remove noise and other harmonics. The primary focus of the Special Issue will be on applications of advanced signal processing and circuit analysis techniques in machine fault diagnostics, energy management, e-health systems, heterogeneous networks, fiber optics, modern communication channels, environment forecasting and resource management. Furthermore, the Special Issue will also invite the latest research in the integration of hardware and software technologies, Artificial Intelligence (AI), Internet of Things (IoT) and microelectronics applications in smart cities. Therefore, this Special Issue will focus on, but not be limited to, the following topics:

  • Advanced signal and image processing techniques
  • Advanced video processing techniques
  • Advances in semi-conductor devices
  • Microelectronic circuit analysis
  • Sensor measurements
  • Communication infrastructure for the IoT
  • Calibration of electronic instruments
  • Smart sensors for machine fault analysis
  • Digital technologies for energy measurement and management systems
  • Digital technologies for health management
  • AI and IoT for smart healthcare
  • Advanced circuits for intelligent transportation
  • Optical networks

Dr. Adam Glowacz
Dr. Muhammad Irfan
Dr. Thompson Sarkodie-Gyan
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 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

  • signal processing
  • image processing
  • sensor measurements
  • microelectronic circuits
  • circuit analysis
  • machine learning
  • deep learning
  • big data analytics
  • intelligent transportation
  • internet of things
  • waste management
  • heterogeneous networks
  • optical networks

Published Papers (4 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

19 pages, 963 KiB  
Article
Robust Spectrum Sensing Detector Based on MIMO Cognitive Radios with Non-Perfect Channel Gain
by Muthana Al-Amidie, Ahmed Al-Asadi, Amjad J. Humaidi, Ayad Al-Dujaili, Laith Alzubaidi, Laith Farhan, Mohammed A. Fadhel, Ronald G. McGarvey and Naz E. Islam
Electronics 2021, 10(5), 529; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10050529 - 24 Feb 2021
Cited by 7 | Viewed by 1941
Abstract
The spectrum has increasingly become occupied by various wireless technologies. For this reason, the spectrum has become a scarce resource. In prior work, the authors have addressed the spectrum sensing problem by using multi-input and multi-output (MIMO) in cognitive radio systems. We considered [...] Read more.
The spectrum has increasingly become occupied by various wireless technologies. For this reason, the spectrum has become a scarce resource. In prior work, the authors have addressed the spectrum sensing problem by using multi-input and multi-output (MIMO) in cognitive radio systems. We considered the detection and estimation framework for MIMO cognitive network where the noise covariance matrix is unknown with perfect channel state information. In this study, we propose a generalized likelihood ratio test (GLRT) for the spectrum sensing problem in cognitive radio where the noise covariance matrix is unknown with non-perfect channel state information. Two scenarios are examined in this study: (i) in the first scenario, the sub-optimal solution of the worst case of the system’s performance is considered; (ii) in the second scenario, we present a robust detector for the MIMO spectrum sensing problem. For both scenarios, the Bayesian approach with a generalized likelihood ratio test based on the binary hypothesis problem is used. From the results, it can be seen that our approach provides the best performance in the spectrum sensing problem under specified assumptions. The simulation results also demonstrate that our approach significantly outperforms other state-of-the-art spectrum sensing detectors when the channel uncertainty is addressed. Full article
(This article belongs to the Special Issue Advanced Signal Processing and Circuit Analysis)
Show Figures

Figure 1

17 pages, 2760 KiB  
Article
Effective Beamforming Technique Amid Optimal Value for Wireless Communication
by Zahid Hussain Qaisar, Muhamamd Irfan, Tariq Ali, Ashfaq Ahmad, Ghulam Ali, Adam Glowacz, Witold Glowacz, Wahyu Caesarendra, Aisha Mousa Mashraqi, Umar Draz and Shafiq Hussain
Electronics 2020, 9(11), 1869; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9111869 - 06 Nov 2020
Cited by 11 | Viewed by 1967
Abstract
In the notion of communication system resource provision specifically, beam-forming is a concept of proficient utilization of the power of transmission. Network densification and massive MIMO allows us to control the power efficiency and can be effectively distributed among different users by reducing [...] Read more.
In the notion of communication system resource provision specifically, beam-forming is a concept of proficient utilization of the power of transmission. Network densification and massive MIMO allows us to control the power efficiency and can be effectively distributed among different users by reducing cost. We presented a practical scenario for the performance of massive MIMO and multi-small cell system to analyze the overall performance of the system. Our work is based on the resource allocation with optimal structural constraints to maintain the cost effectiveness while considering economic implications. The base stations located far away from the users receive attenuated signals and give rise to path loss, whereas the problems of inter cell interference also arise due to transmission from a base station to others cells. The performance of the cellular system can be enhanced with the combination of massive Mimo and small cells, where we simulate and also provide an analysis on practical system with optimal and low complexity beam-forming. The proposed scenario illustrates a structure with an optimal linear transmit beamforming regarding an efficient number of parameters to not lose optimality, which is extendable to designate any specific cellular network in consideration. Our approach exploited schemes with low complexity that are facilitating in complete solution formation, and tested them in various and all possible cases and scenarios. Full article
(This article belongs to the Special Issue Advanced Signal Processing and Circuit Analysis)
Show Figures

Figure 1

18 pages, 2469 KiB  
Article
Savior: A Reliable Fault Resilient Router Architecture for Network-on-Chip
by Ayaz Hussain, Muhammad Irfan, Naveed Khan Baloch, Umar Draz, Tariq Ali, Adam Glowacz, Larisa Dunai and Jose Antonino-Daviu
Electronics 2020, 9(11), 1783; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9111783 - 27 Oct 2020
Cited by 5 | Viewed by 2090
Abstract
The router plays an important role in communication among different processing cores in on-chip networks. Technology scaling on one hand has enabled the designers to integrate multiple processing components on a single chip; on the other hand, it becomes the reason for faults. [...] Read more.
The router plays an important role in communication among different processing cores in on-chip networks. Technology scaling on one hand has enabled the designers to integrate multiple processing components on a single chip; on the other hand, it becomes the reason for faults. A generic router consists of the buffers and pipeline stages. A single fault may result in an undesirable situation of degraded performance or a whole chip may stop working. Therefore, it is necessary to provide permanent fault tolerance to all the components of the router. In this paper, we propose a mechanism that can tolerate permanent faults that occur in the router. We exploit the fault-tolerant techniques of resource sharing and paring between components for the input port unit and routing computation (RC) unit, the resource borrowing for virtual channel allocator (VA) and multiple paths for switch allocator (SA) and crossbar (XB). The experimental results and analysis show that the proposed mechanism enhances the reliability of the router architecture towards permanent faults at the cost of 29% area overhead. The proposed router architecture achieves the highest Silicon Protection Factor (SPF) metric, which is 24.8 as compared to the state-of-the-art fault-tolerant architectures. It incurs an increase in latency for SPLASH2 and PARSEC benchmark traffics, which is minimal as compared to the baseline router. Full article
(This article belongs to the Special Issue Advanced Signal Processing and Circuit Analysis)
Show Figures

Figure 1

12 pages, 3795 KiB  
Article
Three-Dimensional Reconstruction of Fleece Fabric Surface for Thickness Evaluation
by Shoufeng Jin, Yang Chen, Jiajie Yin, Yi Li, Munish Kumar Gupta, Pawel Fracz and Zhixiong Li
Electronics 2020, 9(9), 1346; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics9091346 - 20 Aug 2020
Cited by 2 | Viewed by 2080
Abstract
Aiming at solving the problem of manually measuring the fabric surface thickness, this paper proposes a three-dimensional (3D) reconstruction method based on the tangential two-dimensional (2D) sequence images. Firstly, the characteristic region of the fabric surface is extracted. Secondly, the image is splitting [...] Read more.
Aiming at solving the problem of manually measuring the fabric surface thickness, this paper proposes a three-dimensional (3D) reconstruction method based on the tangential two-dimensional (2D) sequence images. Firstly, the characteristic region of the fabric surface is extracted. Secondly, the image is splitting based on the maximum between-class variance method. Thirdly, the splitting image is processed by the morphological method. Fourthly, the canny operator is used to obtain the edge detection for calculating the edge contour coordinate. Finally, the surf function is used to reconstruct the 3D model of the fabric surface. To evaluate the performance of the proposed 3D model, the thickness and relief degree of the fabric surface are used, and the comparison between the proposed method and the manual measurement is carried out. The results demonstrate that, under a reasonable relief degree condition, the proposed method is more effective to evaluate the thickness of the fabric surface and the estimated thickness is more accurate than the manually measured one. Full article
(This article belongs to the Special Issue Advanced Signal Processing and Circuit Analysis)
Show Figures

Figure 1

Back to TopTop