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International Conference on Intelligent System and Knowledge engineering, ISKE

作者： Jiajie Zhou Shunzhan He Hongqiang Mo Xiang Tian Zhong Li School of Automation Science and Engineering South China University of Technology Guangzhou China School of Electronic and Information Engineering South China University of Technology Guangzhou China Faculty of Mathematics and Computer Science FernUniversitaet in Hagen Hagen Germany

ISBN: (数字)9781728123486

ISBN: (纸本)9781728123493

Dual microphone adaptive filters (DMAFs) whose parameters are optimized with normalized least mean squares (NLMS) algorithms have been widely used to reduce uncertain ambient noises. However, when used in auscultation, they are prone to periodic misalignment of the parameters caused by high filtering error. In this paper, a modified DMAF is proposed to solve this problem. A high-pass filter is introduced as signal preprocessing to reduce the amplitudes of the first and second heart sounds, and correspondingly, the filtering error. The preprocessed signals are fed into an adaptive filter, and the output of the adaptive filter is then low-pass filtered to restore the pure heart sounds. In this way, a lower steady state misalignment can be achieved. Simulation results showed that, the modified DMAF significantly outperformed the traditional DMAF on parameter alignment and signal-to-noise ratio.

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Theatre, love and graphs 17

Theatre, love and graphs

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17th Conference on Applied Mathematics, APLIMAT 2018

作者： Zawislak, Stanislaw Kopec, Jerzy Department of Informatics and Automation Faculty of Mechanical Engineering and Computer Science University of Bielsko-Biala Willowa 2 Bielsko-Biala43-309 Poland Department of Machine Building Faculty of Mechanical Engineering and Computer Science University of Bielsko-Biala Willowa 2 Bielsko-Biala43-309 Poland

ISBN: (纸本)9788022747653

In the paper, utilization of graphs in theatre-related issues is discussed. World-wide known plays are analysed: W. Shakespeare's "Measure for measure", M. Camoletti's "Boeing, Boeing" and Jaroslaw Murawski's "Humanka". The graphs represent relations among the heroes however they could be a part of scenography. Graph-based modelling allows for deeper understanding of attitudes and dependencies between dramatis personae, additionally unexpected visions of the plot are obtained. © 2018 Slovak University of Technology in Bratislava. All rights reserved.

关键词： Clique Deeper understanding Independent set Maggraph Plot

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Mathematical modeling of the two-stage chaotic colpitis oscillator 14

Mathematical modeling of the two-stage chaotic colpitis osci...

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14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2018

作者： Semenov, Andriy O. Savytskyi, Anton Yu. Bisikalo, Oleg V. Kulakov, Pavlo I. Dept. of Radio-Frequency Engineering Vinnytsia National Technical University Vinnytsia Ukraine Faculty for Computer Systems and Automation Vinnytsia National Technical University Vinnytsia Ukraine

ISBN: (纸本)9781538625569

The mathematical modeling of the Chaotic Colpitts Oscillator with two stages is carried out in the paper. The following results of mathematical modeling are obtained: oscillator's phase portrait in the planes of normalized dynamic variables;oscillator's phase portraits in the spaces of normalized dynamic variables;time diagrams of generated chaotic oscillations;amplitude-frequency and phase-frequency characteristics of generated chaotic oscillations. © 2018 IEEE.

关键词： Oscillators Mathematical model Oscillators mathematical modeling Mathematical Model Amplitude plane Colpitts oscillator

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Numerical Study of Differential Temperature Measurement in Human Muscle Tissue using UWB Radar

Numerical Study of Differential Temperature Measurement in H...

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European Conference on Antennas and Propagation

作者： Ondrej Fiser Vojtech Hruby Sebastian Ley Marko Helbig Jürgen Sachs Jan Vrba Department of Biomedical Technology Faculty of Biomedical Engineering Czech Technical University in Prague Czech Republic Department of Electromagnetic Field Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Institute of Biomedical Engineering and Informatics Faculty of Computer Science and Automation Technische Universität Ilmenau Germany Institute of Information Technology Faculty of Electrical Engineering and Information Technology Technische Universität Ilmenau Germany

This paper deals with the numerical study of the differential temperature measurement by means of ultra-wide band (UWB) radar in the muscle tissue. The temperature range of interest corresponds to the hyperthermia tumor treatment (up to 45 ℃). A 1D model based on Mason graphs and a simplified sandwich structure is introduced to observe the expected usable frequency band and differential signal dependence on the temperature change. Results show a linear dependence of the received radar signals on temperature change in the human muscle phantom. We numerically proved that it is possible to detect temperature changes inside the UWB signals backscattered from the heated region.

关键词： Temperature measurement Temperature dependence Hyperthermia Muscles Phantoms Electromagnetic heating

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Sensitivity analysis of digital filters using the continued fraction expansion 1

Sensitivity analysis of digital filters using the continued ...

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1st Moscow Workshop on Electronic and Networking Technologies, MWENT 2018

作者： Lesnikov, V. Naumovich, T. Chastikov, A. Department of Radioelectronic Means Faculty of Automation and Computer Engineering Institute of Mathematics and Information Systems Vyatka State University Moscow str. 36 Kirov610000 Russia

ISBN: (纸本)9781538634974

It is known that many structural schemes can be used to implement digital filters. Some structures of digital filters are characterized by low sensitivity of the characteristics to the accuracy of the representation of the coefficients. A separate group of methods for the structural synthesis of digital filters is based on the expansion of rational fractions, including transfer functions, into continued fractions. Because of this decomposition, ladder structures are obtained. The sensitivity of such ladder structures is analyzed in this paper. As a measure of the structure sensitivity, estimations of the partial derivatives of the transfer function coefficients with respect to the expansion coefficients in continued fraction were used. The analysis showed that the sensitivity of the transfer function coefficients to some expansion coefficients is very small. However, the presented examples show that the sensitivity to certain coefficients of expansion can exceed the sensitivity of the classical direct and the canonic forms. © 2018 IEEE.

关键词： IIR filters

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Preface

Lecture Notes in Networks and Systems

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Lecture Notes in Networks and Systems 2023年 764 LNNS卷 v-vi页

作者： Milrad, Marcelo Otero, Nuno Sánchez-Gómez, María Cruz Mena, Juan José Durães, Dalila Sciarrone, Filippo Alvarez-Gómez, Claudio Rodrigues, Manuel Vittorini, Pierpaolo Gennari, Rosella Di Mascio, Tania Temperini, Marco De la Prieta, Fernando Linnaeus University Växjö Sweden University of Greenwich London United Kingdom Department of Didactics Organization and Research Method University of Salamanca Salamanca Spain University of Minho Braga Portugal Mercatorum University Rome Italy Facultad de Ingeniería y Ciencias Aplicadas Universidad de los Andes Santiago Chile Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Faculty of Computer Science Free University of Bozen-Bolzano Bolzano Italy Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Dipartimento di Ingegneria Informatica Sapienza Universita’ di Roma Rome Italy Department of Computer Science and Automation Control University of Salamanca Salamanca Spain

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Predicting protein functions through non-negative matrix factorization regularized by protein-protein interaction network and gene functional information

Predicting protein functions through non-negative matrix fac...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Wei Peng Lun Li Wei Dai Jielin Du Wei Lan Faculty of Information Engineering and Automation Kunming University of Science and Technology Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming China School of Computer Electronic and Information Guangxi University Guangxi University Nanning China

Protein function prediction is necessary for understanding life and is valuable for application on drug design and health care. It is still a big challenge to predict protein function correctly by integrating multi-biological information. In this work, we propose a novel non-Negative Matrix Factorization (NMF) based method regularized by PPI network and GO similarity network, namely PONMF, for protein function prediction, which decomposes the known GO-protein association matrix into two low-rank matrixes for proteins and GO terms. In the course of factorization, PONMF incorporates the label matrix factorization term, an additional network regularization term and a GO similarity regularization term into the objective function. Finally, the potential protein functions are predicted by referring to the product of the two low-rank matrixes. PONMF not only successfully integrates diverse biological information to predict protein functions, but also naturally partitions proteins into different modules and infers functions from the proteins in the same modules. Our methods as well as the other two state-of-the-art methods (UBiRW and NMFGO) are applied to predict functions for protein of S. cerevisiae and H. sapiens. The prediction results show that PONMF outperforms the other two existing methods.

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Modal regression based structured low-rank matrix recovery for multi-view learning

arXiv

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arXiv 2020年

作者： Xu, Jiamiao Wang, Fangzhao Peng, Qinmu You, Xinge Wang, Shuo Jing, Xiao-Yuan Philip Chen, C.L. School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute China State Key Laboratory of Software Engineering School of Computer Wuhan University China Department of Computer and Information Science Faculty of Science and Technology University of Macau 99999 China Dalian Maritime University Dalian116026 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods are incapable of well handling view discrepancy and discriminancy simultaneously, which thus leads to the performance degradation when there is a large discrepancy among multi-view data. To circumvent this drawback, motivated by the block-diagonal representation learning, we propose Structured Low-rank Matrix Recovery (SLMR), a unique method of effectively removing view discrepancy and improving discriminancy through the recovery of structured low-rank matrix. Furthermore, recent low-rank modeling provides a satisfactory solution to address data contaminated by predefined assumptions of noise distribution, such as Gaussian or Laplacian distribution. However, these models are not practical since complicated noise in practice may violate those assumptions and the distribution is generally unknown in advance. To alleviate such limitation, modal regression is elegantly incorporated into the framework of SLMR (term it MR-SLMR). Different from previous LMvSL based methods, our MR-SLMR can handle any zero-mode noise variable that contains a wide range of noise, such as Gaussian noise, random noise and outliers. The alternating direction method of multipliers (ADMM) framework and half-quadratic theory are used to efficiently optimize MR-SLMR. Experimental results on four public databases demonstrate the superiority of MR-SLMR and its robustness to complicated noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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A block sparsity based estimator for mmwave massive MIMO channels with beam squint

arXiv

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arXiv 2019年

作者： Wang, Mingjin Gao, Feifei Flanagan, Mark F. Shlezinger, Nir Eldar, Yonina C. Department of Automation Tsinghua University Beijing China School of Electrical and Electronic Engineering University College Dublin Belfield Dublin 4 Ireland Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel

Multiple-input multiple-output (MIMO) millimeter wave (mmWave) communication is a key technology for next generation wireless networks. One of the consequences of utilizing a large number of antennas with an increased bandwidth is that array steering vectors vary among different subcarriers. Due to this effect, known as beam squint, the conventional channel model is no longer applicable for mmWave massive MIMO systems. In this paper, we study channel estimation under the resulting non-standard model. To that aim, we first analyze the beam squint effect from an array signal processing perspective, resulting in a model which sheds light on the angle-delay sparsity of mmWave transmission. We next design a compressive sensing based channel estimation algorithm which utilizes the shift-invariant block-sparsity of this channel model. The proposed algorithm jointly computes the off-grid angles, the off-grid delays, and the complex gains of the multi-path channel. We show that the newly proposed scheme reflects the mmWave channel more accurately and results in improved performance compared to traditional approaches. We then demonstrate how this approach can be applied to recover both the uplink as well as the downlink channel in frequency division duplex (FDD) systems, by exploiting the angle-delay reciprocity of mmWave channels. Copyright © 2019, The Authors. All rights reserved.

关键词： MIMO systems

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A novel approach for protection of accounts’ names against hackers combining cluster analysis and chaotic theory

arXiv

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arXiv 2019年

作者： Andreev, Desislav Petrakieva, Simona Taralova, Ina Dep. Computer Science Faculty of Computer Systems and Technologies Technical University of Sofia Dep. Theory of Electrical Engineering Faculty of Automation Technical University of Sofia Laboratoire des Sciences du Numérique de Nantes LS2N UMR 6004 Ecole Centrale de Nantes

The last years of the 20th century and the beginning of the 21th mark the facilitation trend of our real life due to the big development and progress of the computers and other intelligent devices. Algorithms based on artificial intelligence are basically a part of the software. The transmitted information by Internet or LAN arises continuously and it is expected that the protection of the data has been ensured. The aim of the present paper is to reveal false names of users’ accounts as a result of hackers’ attacks. The probability a given account to be either false or actual is calculated using a novel approach combining machine learning analysis (especially clusters’ analysis) with chaos theory. The suspected account will be used as a pattern and by classification techniques clusters will be formed with a respective probability this name to be false. This investigation puts two main purposes: First, to determine if there exists a trend of appearance of the similar usernames, which arises during the creation of new accounts. Second, to detect the false usernames and to discriminate those from the real ones, independently of that if two types of accounts are generated with the same speed. These security systems are applied in different areas, where the security of the data in users’ accounts is strictly required. For example, they can be used in on-line voting for balloting, in studying the social opinion by inquiries, in protection of the information in different user accounts of given system etc. Copyright © 2019, The Authors. All rights reserved.

关键词： Cluster analysis

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