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Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP)

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 26920

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Assoc. Prof. Norbert Herencsar

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Department of Telecommunications, Brno University of Technology, Technicka 3082/12, 616 00 Brno, Czech Republic
Interests: analog electronics; analog filters; circuit theory; current-mode circuits; fractional-order components and systems synthesis; MOS-only circuits
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Dr. Francesco Benedetto

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Signal Processing for Telecommunications and Economics Laboratory, Economics Department, University of ROMA TRE, Via Silvio D'Amico 77, 00145 Rome, Italy
Interests: ground-penetrating radar; radar signal processing; software and cognitive radio; digital signal and image processing for telecommunications and economics
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Prof. Dr. Jorge Crichigno

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College of Engineering and Computing, University of South Carolina, Innovation Center, 550 Assembly Street, Suite 1300, Columbia, SC 29208, USA
Interests: wireless and optical networks; graph theory; mathematical optimization; network security
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Special Issue Information

Dear Colleagues,

The 43rd (2020) to 45th (2022) International Conference on Telecommunications and Signal Processing (TSP - http://tsp.vutbr.cz/) have been organized virtually by eighteen universities from the Czech Republic, Hungary, Turkey, Croatia, Taiwan, Japan, Slovak Republic, Spain, Bulgaria, France, Romania, Slovenia, Greece, and Poland, for academics, researchers, and developers. This conference serves as a premier annual international forum to promote the exchange of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors worldwide. Authors of selected high-quality research papers will be invited to submit their extended versions for publishing in the Special Issue, "Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP)" in Applied Sciences.

Assoc. Prof. Norbert Herencsar
Prof. Dr. Francesco Benedetto
Prof. Dr. Jorge Crichigno
Guest Editors

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Keywords

telecommunications
information systems
network services
network technologies
telecommunication systems
simulation and measurement
analog signal processing
audio signal processing
biomedical signal processing
digital signal processing
image and video signal processing
speech and language processing

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Published Papers (9 papers)

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Research

20 pages, 6426 KiB

Open AccessArticle

Stress Level Detection and Evaluation from Phonation and PPG Signals Recorded in an Open-Air MRI Device

by Jiří Přibil, Anna Přibilová and Ivan Frollo

Appl. Sci. 2021, 11(24), 11748; https://doi.org/10.3390/app112411748 - 10 Dec 2021

Cited by 3 | Viewed by 3242

Abstract

This paper deals with two modalities for stress detection and evaluation—vowel phonation speech signal and photo-plethysmography (PPG) signal. The main measurement is carried out in four phases representing different stress conditions for the tested person. The first and last phases are realized in laboratory conditions. The PPG and phonation signals are recorded inside the magnetic resonance imaging scanner working with a weak magnetic field up to 0.2 T in a silent state and/or with a running scan sequence during the middle two phases. From the recorded phonation signal, different speech features are determined for statistical analysis and evaluation by the Gaussian mixture models (GMM) classifier. A database of affective sounds and two databases of emotional speech were used for GMM creation and training. The second part of the developed method gives comparison of results obtained from the statistical description of the sensed PPG wave together with the determined heart rate and Oliva–Roztocil index values. The fusion of results obtained from both modalities gives the final stress level. The performed experiments confirm our working assumption that a fusion of both types of analysis is usable for this task—the final stress level values give better results than the speech or PPG signals alone. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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17 pages, 4970 KiB

Open AccessArticle

Multi-Input Convolutional Neural Networks for Automatic Pollen Classification

by Mihai Boldeanu, Horia Cucu, Corneliu Burileanu and Luminița Mărmureanu

Appl. Sci. 2021, 11(24), 11707; https://doi.org/10.3390/app112411707 - 9 Dec 2021

Cited by 6 | Viewed by 2388

Abstract

Pollen allergies are a cause of much suffering for an increasing number of individuals. Current pollen monitoring techniques are lacking due to their reliance on manual counting and classification of pollen by human technicians. In this study, we present a neural network architecture capable of distinguishing pollen species using data from an automated particle measurement device. This work presents an improvement over the current state of the art in the task of automated pollen classification, using fluorescence spectrum data of aerosol particles. We obtained a relative reduction in the error rate of over 48%, from 27% to 14%, for one of the datasets, with similar improvements for the other analyzed datasets. We also use a novel approach for doing hyperparameter tuning for multiple input networks. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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15 pages, 366 KiB

Open AccessArticle

Quaternion Codes in MIMO System of Dual-Polarized Antennas

by Sajid Ali, Sara Shakil Qureshi and Syed Ali Hassan

Appl. Sci. 2021, 11(7), 3131; https://doi.org/10.3390/app11073131 - 1 Apr 2021

Viewed by 1912

Abstract

The use of quaternion orthogonal designs (QODs) to describe point-to-point communication among dual-polarized antennas has the potential to provide higher rate orthogonal and quasi-orthogonal complex designs exploiting polarization diversity among space and time diversities. Furthermore, it is essential to have a space time block code (STBC) which offers a linear and decoupled decoder which quasi-orthogonal designs fail to attain. In this paper, we show how the realm of quaternions unexpectedly offers us a possible solution and codes obtained from quaternion designs mostly achieve both linear and decoupled decoders. This motivated us to perform an indispensable search for QODs such that the code rate is bounded below by 1/2 and does not sharply decrease as the number of transmit antennas increases. It is shown that three famous recursive techniques do not satisfy this criteria and their code rates decrease rather rapidly. Therefore, we propose another method of constructing quaternion designs suitable for any number of transmit antennas and verify that these attain linear and decoupled decoders with the system model based on quaternionic channel. It is shown that such designs outperform others in terms of transmit diversity, code rates and the optimality of the proposed decoder is validated through simulation results. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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21 pages, 1278 KiB

Open AccessArticle

Time-Dependent Performance of a Multi-Hop Software Defined Network

by Tadeusz Czachórski, Erol Gelenbe, Godlove Suila Kuaban and Dariusz Marek

Appl. Sci. 2021, 11(6), 2469; https://doi.org/10.3390/app11062469 - 10 Mar 2021

Cited by 14 | Viewed by 2536

Abstract

It has been recently observed that Software Defined Networks (SDN) can change the paths of different connections in the network at a relatively frequent pace to improve the overall network performance, including delay and packet loss, or to respond to other needs such as security. These changes mean that a network that SDN controls will seldom operate in steady state; rather, the network may often be in transient mode, especially when the network is heavily loaded and path changes are critically important. Hence, we propose a transient analysis of such networks to better understand how frequent changes in paths and the switches’ workloads may affect multi-hop networks’ performance. Since conventional queueing models are difficult to solve for transient behaviour and simulations take excessive computation time due to the need for statistical accuracy, we use a diffusion approximation to study a multi-hop network controlled by SDN. The results show that network optimization should consider the transient effects of SDN and that transients need to be included in the design of algorithms for SDN controllers that optimize network performance. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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17 pages, 1123 KiB

Open AccessArticle

Iterative Receiver Design for the Estimation of Gaussian Samples in Impulsive Noise

by Anoush Mirbadin, Armando Vannucci, Giulio Colavolpe, Riccardo Pecori and Luca Veltri

Appl. Sci. 2021, 11(2), 557; https://doi.org/10.3390/app11020557 - 8 Jan 2021

Cited by 3 | Viewed by 1686

Abstract

Impulsive noise is the main limiting factor for transmission over channels affected by electromagnetic interference. We study the estimation of (correlated) Gaussian signals in an impulsive noise scenario. In this work, we analyze some of the existing, as well as some novel estimation algorithms. Their performance is compared, for the first time, for different channel conditions, including the Markov–Middleton scenario, where the impulsive noise switches between different noise states. Following a modern approach in digital communications, the receiver design is based on a factor graph model and implements a message passing algorithm. The correlation among signal samples, as well as among noise states brings about a loopy factor graph, where an iterative message passing scheme should be employed. As is well known, approximate variational inference techniques are necessary in these cases. We propose and analyze different algorithms and provide a complete performance comparison among them, showing that the expectation propagation, transparent propagation, and parallel iterative schedule approaches reach a performance close to optimal, at different channel conditions. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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19 pages, 2874 KiB

Open AccessArticle

Improving the Targets’ Trajectories Estimated by an Automotive RADAR Sensor Using Polynomial Fitting

by Georgiana Magu, Radu Lucaciu and Alexandru Isar

Appl. Sci. 2021, 11(1), 361; https://doi.org/10.3390/app11010361 - 1 Jan 2021

Cited by 3 | Viewed by 2455

Abstract

A way to reduce the uncertainty at the output of a Kalman filter embedded into a tracker connected to an automotive RADAR sensor consists of the adaptive selection of parameters during the tracking process. Different informed strategies for automatically tuning the tracker’s parameters and to jointly learn the parameters and state/output sequence using: expectation maximization; optimization approaches, including the simplex algorithm; coordinate descent; genetic algorithms; nonlinear programming using finite differencing to estimate the gradient; Bayesian optimization and reinforcement learning; automatically tuning hyper-parameters in the least squares, were already proposed. We develop here a different semi-blind post-processing approach, which is faster and more robust. Starting from the conjecture that the trajectory is polynomial in Cartesian coordinates, our method supposes to fit the data obtained at the output of the tracker to a polynomial. We highlight, by simulations, the improvement of the estimated trajectory’s accuracy using the polynomial fitting for single and multiple targets. We propose a new polynomial fitting method based on wavelets in two steps: denoising and polynomial part extraction, which compares favorably with the classical polynomial fitting method. The effect of the proposed post-processing methods is visible, the accuracy of targets’ trajectories estimations being hardly increased. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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19 pages, 6690 KiB

Open AccessArticle

Optimized Design of OTA-Based Gyrator Realizing Fractional-Order Inductance Simulator: A Comprehensive Analysis

by David Kubanek, Jaroslav Koton, Jan Dvorak, Norbert Herencsar and Roman Sotner

Appl. Sci. 2021, 11(1), 291; https://doi.org/10.3390/app11010291 - 30 Dec 2020

Cited by 9 | Viewed by 2824

Abstract

A detailed analysis of an operational transconductance amplifier based gyrator implementing a fractional-order inductance simulator is presented. The influence of active element non-ideal properties on the gyrator operation is investigated and demonstrated by admittance characteristics and formulas for important values and cut-off frequencies in these characteristics. Recommendations to optimize the performance of the gyrator in terms of operation bandwidth, the range of obtainable admittance magnitude, and signal dynamic range are proposed. The theoretical observations are verified by PSpice simulations of the gyrator with LT1228 integrated circuit. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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31 pages, 11660 KiB

Open AccessArticle

A Novel Wearable Foot and Ankle Monitoring System for the Assessment of Gait Biomechanics

by Paul Faragó, Lăcrimioara Grama, Monica-Adriana Farago and Sorin Hintea

Appl. Sci. 2021, 11(1), 268; https://doi.org/10.3390/app11010268 - 29 Dec 2020

Cited by 13 | Viewed by 5192

Abstract

Walking is the most basic form of human activity for achieving mobility. As an essential function of the human body, the examination of walking is directed towards the assessment of body mechanics in posture and during movement. This work proposes a wearable smart system for the monitoring and objective evaluation of foot biomechanics during gait. The proposed solution assumes the cross-correlation of the plantar pressure with lower-limb muscular activity, throughout the stance phase of walking. Plantar pressure is acquired with an array of resistive pressure sensors deployed onto a shoe insole along the center of gravity progression line. Lower-limb muscular activity is determined from the electromyogram of the tibialis anterior and gastrocnemius lower limb muscles respectively. Under this scenario, physiological gait assumes the interdependency of plantar pressure on the heel area with activation of the tibialis anterior, as well as plantar pressure on the metatarsal arch/toe area with activation of the gastrocnemius. As such, assessment of gait physiology is performed by comparison of a gait map, formulated based on the footprint–lower-limb muscle cross-correlation results, to a reference gait template. A laboratory proof of concept validates the proposed solution in a test scenario which assumes a normal walking and two pathological walking patterns. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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18 pages, 4958 KiB

Open AccessArticle

GMM-Based Evaluation of Synthetic Speech Quality Using 2D Classification in Pleasure-Arousal Scale

by Jiří Přibil, Anna Přibilová and Jindřich Matoušek

Appl. Sci. 2021, 11(1), 2; https://doi.org/10.3390/app11010002 - 22 Dec 2020

Cited by 3 | Viewed by 2506

Abstract

The paper focuses on the description of a system for the automatic evaluation of synthetic speech quality based on the Gaussian mixture model (GMM) classifier. The speech material originating from a real speaker is compared with synthesized material to determine similarities or differences between them. The final evaluation order is determined by distances in the Pleasure-Arousal (P-A) space between the original and synthetic speech using different synthesis and/or prosody manipulation methods implemented in the Czech text-to-speech system. The GMM models for continual 2D detection of P-A classes are trained using the sound/speech material from the databases without any relation to the original speech or the synthesized sentences. Preliminary and auxiliary analyses show a substantial influence of the number of mixtures, the number and type of the speech features used the size of the processed speech material, as well as the type of the database used for the creation of the GMMs on the P-A classification process and on the final evaluation result. The main evaluation experiments confirm the functionality of the system developed. The objective evaluation results obtained are principally correlated with the subjective ratings of human evaluators; however, partial differences were indicated, so a subsequent detailed investigation must be performed. Full article

(This article belongs to the Special Issue Selected Papers from the 2020 43rd to 2022 45th International Conference on Telecommunications and Signal Processing (TSP))

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