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2019 International Conference on Internet of Things, Embedded Systems and Communications, IINTEC 2019

作者： Dhibi, Khaled Fezai, Radhia Mansouri, Majdi Kouadri, Abdelmalek Bouzrara, Kais Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir 5019 Tunisia Electrical and Computer Engineering Program Texas AM University at Qatar Doha Qatar

ISBN: (纸本)9781728151847

Process monitoring is an essential part of industrial systems. It requires higher product quality and safety operations. Therefore, a nonlinear data-driven approach based reduced KPCA (RKPCA) for statistical monitoring of industrial processes is developed. RKPCA is a novel machine learning tool which merges dimensionality reduction and supervised learning. The use of classical KPCA for modeling and monitoring purposes can impose a high computational load when a large number of measurements are recorded. The main idea of the proposed RKPCA approach is to reduce the number of observations (samples) in the data matrix using the Euclidean distance between samples as dissimilarity metric so that only one observation is kept in case of redundancy. The Tennessee Eastman Process (TEP) is used to evaluate the fault detection abilities of the proposed RKPCA technique. The performance of the proposed method is evaluated and compared to the classical KPCA in terms of false alarms rates (FAR), missed detection rates (MDR) and computation times (CT). © 2019 IEEE.

关键词： Fault detection

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On the optimal precoding for MIMO gaussian wire-tap channels

On the optimal precoding for MIMO gaussian wire-tap channels

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10th IEEE International Symposium on Wireless Communication Systems 2013, ISWCS 2013

作者： Khabbazibasmenj, Arash Girnyk, Maksym A. Vorobyov, Sergiy A. Vehkaperä, Mikko Rasmussen, Lars K. Department of Electrical and Computer Engineering University of Alberta AB Canada ACCESS Linnaeus Center KTH Royal Institute of Technology School of Electrical Engineering Sweden Department of Signal Processing and Acoustics School of Electrical Engineering Aalto University Finland

ISBN: (纸本)9783800735297

We consider the problem of finding secrecy rate of a multiple-input multiple-output (MIMO) wire-tap channel. A transmitter, a legitimate receiver, and an eavesdropper are all equipped with multiple antennas. The channel states from the transmitter to the legitimate user and to the eavesdropper are assumed to be known at the transmitter. In this contribution, we address the problem of finding the optimal precoder/transmit covariance matrix maximizing the secrecy rate of the given wiretap channel. The problem formulation is shown to be equivalent to a difference of convex functions programming problem and an efficient algorithm for addressing this problem is developed. © VDE Verlag GMBH.

关键词： Transmitters

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Web-based platform for problem-centered learning in DSP

Web-based platform for problem-centered learning in DSP

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IEEE Digital signal processing Workshop

作者： Gregory A. Krudysz James H. McClellan Center of Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology USA

In this paper we present a web-based tutoring system designed to enhance a student's conceptual understanding by providing many concept-centered exercises. The system relies on a course textbook from an introductory signal processing course for knowledge representation, and also on a large database of relevant problems. We construct concept maps from the textbook to create meta-data for various textbook derived resources, as well as for tagging all the exercise questions. The system tracks each student's comprehension of the course material by evaluating the student's problem solving proficiency in terms of the concepts from the textbook..

关键词： Mathematical model Equations Problem-solving Frequency domain analysis Books Indexes

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Fractal interpolation of images and volumes

Fractal interpolation of images and volumes

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Asilomar Conference on signals, Systems & computers

作者： J.R. Price M.H. Hayes Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology USA

We present a method for constructing fractal interpolation surfaces and volumes through points sampled on rectangular lattices. Unlike other surface constructions ours uses rectangular rather than triangular tilings, halving the number of required parameters. This method is no more complex than previous constructions and yet does not suffer from their limitations. Additionally, our construction extends easily to volumetric interpolation, for which there were no previous (continuous) constructions. In addition to an example with synthetic data, a real image is interpolated using a fractal surface. Limitations and possible improvements are mentioned.

关键词： Fractals Interpolation Data visualization signal processing image processing Lattices Surface fitting Rendering (computer graphics) Smoothing methods Speech

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Pruned multi-angle resolution fast beam-forming

Pruned multi-angle resolution fast beam-forming

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IEEE Sensor Array and Multichannel signal processing Workshop, SAME 2002

作者： Yoon, Yeo-Sun Kaplan, Lance M. McClellan, James H. Center for Signal and Image Processing Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA30332-0250 United States Dept. of Engineering CTSPS Clark Atlanta University AtlantaGA303 14 United States

ISBN: (纸本)0780375513

Delay-and-sum (DS) beam-forming is one of the basic beam-forming methods, and it is effective for both narrow- And wide-band sources. However, DS beam-forming exhibits high computational complexity. Recently, a fast multistage approximation of DS beam-forming was introduced. In order to further improve the computational efficiency of the fast beam-former, we have integrated a detector into the intermediate stages of the fast algorithm. This detector can save computations by stopping further processing to resolve benign angular sectors that do not contain a coherent source. The joint fast detector beam-former was tested using various wideband signals such as spread spectrum signals used in wireless communications. This technique should provide a useful direction finding solution in wireless communications and target localization applications. In addition, the fast algorithm can find initial values for high resolution direction-of-arrivals estimators such as coherent signal subspace methods. © 2002 IEEE.

关键词： Computational efficiency

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A secure communications system using chaotic switching

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INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS 1997年第6期7卷 1383-1394页

作者： Lee, C Williams, DB Lee, J Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332-0250 USA

Since previous secure communications methods using chaotic systems require very high SNRs, knowledge of the initial conditions, and/or chaotic systems with the self-synchronization property, their application is limited. In this paper, a new secure communications scheme based on chaotic switching is discussed. The proposed scheme makes decisions on the incoming bits by comparing the power level of the dynamical error for each symbol signal after applying a noise reduction method based on the known system dynamics. A multi-user secure communications scheme is also considered where each user's symbol signal is mapped through a unique scramble matrix. We also examine whether these scramble matrices help to combat against smart jamming. The proposed system does not require self-synchronization between the chaotic receiver and transmitter and exhibits Seasonable performance at relatively low SNRs.

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A C++ research and development environment for speech and audio processing applications

A C++ research and development environment for speech and au...

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34th Asilomar Conference

作者： Erdem Ertan, A. Barnwell III, T.P. School of Elec./Computer Engineering Center for Signal/Image Processing Georgia Institute of Technology 250 14th Street NW Atlanta GA 30318 United States

Speech and audio processing algorithms, which are based on the processing of the features and signals, are often written using poor programming styles. Understanding the existing source code and extending it is thus a time-consuming process that forces researchers to deal with programming problems instead of speech and audio processing innovations. We have developed a new system in C++ to overcome these problems. The programming techniques used in this environment allow a researcher to concentrate on innovations in an environment that still allows the rapid implementation of efficient real-time speech and audio processing applications.

关键词： Speech processing

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

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2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010

作者： Ramezani, Mahdi Heidari, Amin Fatemizadeh, Emad Soltanian-Zadeh, Hamid Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI 48202 United States Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

ISBN: (纸本)9781424466238

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearestneighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Brain

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Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm

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Energy Reports 2023年 10卷 3113-3124页

作者： Attouri, Khadija Dhibi, Khaled Mansouri, Majdi Hajji, Mansour Bouzrara, Kais Nounou, Mohamed Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kasserine1200 Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Qatar Chemical Engineering Program Texas A&M University at Qatar Qatar Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir University of Monastir 5019 Tunisia

This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. The approach unfolds in three integral phases. Firstly, the establishment of interval centers and ranges, employing upper and lower bounds, effectively manages the inherent uncertainties arising from noise and measurement errors intrinsic to the wind system. Subsequently, the dataset undergoes processing via the Sine-Cosine Optimization Algorithm (SCOA), enabling the extraction of the most pertinent attributes. The culmination of predictive precision and classification performance is achieved through the integration of the refined dataset into an ensemble learning paradigm, harmonizing bagging, boosting techniques, and an artificial neural network classifier. The principal aim of the IEL-SCOA approach is to discern the spectrum of operational conditions within WEC systems, encompassing a healthy mode alongside six distinct faulty modes. These anomalies, encompassing short circuits, open circuits, and wear-out incidents, are deliberately induced at diverse locations and facets of the system, notably the generator and grid sides. Empirical results underscore the robustness and efficiency of the proposed methodology, showcasing an exceptional accuracy rate of 99.76 %. These outcomes definitively establish the IEL-SCOA approach as a potent and efficacious tool for precise fault diagnosis in uncertain WEC systems. © 2023

关键词： Fault detection

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A robust algorithm for automatic target recognition using passive radar

A robust algorithm for automatic target recognition using pa...

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Southeastern Symposium on System Theory

作者： L.M. Ehrman A.D. Lanterman Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Center for Signal and Image Processing Georgia Institute of Technology Altanta GA

The goal of this research is to add automatic target recognition (ATR) capabilities to existing passive radar systems. We do so by comparing the radar cross section (RCS) of detected targets to the precomputed RCS of known targets in the target class. The precomputed RCS of the targets comprising the target class is modeled using a multi-step process involving programs such as the fast Illinois solver code (FISC). Advanced refractive effects prediction system (AREPS) and numerical electromagnetic code (NEC2). A Rician likelihood model compares the power profile of the detected target to the precomputed power profiles of the targets in the target class; this comparison results in target identification. Thus far, the results of simulations are encouraging, indicating that the algorithm correctly identifies aircraft with high probability at the anticipated noise level. Performance can be expected to decline as the noise power surpasses the maximum signal power.

关键词： Robustness Target recognition Passive radar Power system modeling Radar cross section Radar detection Electromagnetic refraction Rician channels Aircraft Noise level

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