Conferences related to Matrices

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2019 IEEE 28th International Symposium on Industrial Electronics (ISIE)

The conference will provide a forum for discussions and presentations of advancements inknowledge, new methods and technologies relevant to industrial electronics, along with their applications and future developments.

2019 IEEE 46th Photovoltaic Specialists Conference (PVSC)

Photovoltaic materials, devices, systems and related science and technology

2019 IEEE 58th Conference on Decision and Control (CDC)

The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.The 58th CDC will feature contributed and invited papers, as well as workshops and may include tutorial sessions.The IEEE CDC is hosted by the IEEE Control Systems Society (CSS) in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).

2019 IEEE 69th Electronic Components and Technology Conference (ECTC)

premier components, packaging and technology conference

2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

The conference is intended to provide an international forum for the exchange of information on state-of-the-art research in antennas, propagation, electromagnetics, and radio science.

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Periodicals related to Matrices

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.

Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission

Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...

Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.

Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...

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Most published Xplore authors for Matrices

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Xplore Articles related to Matrices

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A high performance multifrontal code for linear solution of structures using multi-core microprocessors

[{u'author_order': 1, u'affiliation': u'Computer Aided Structural Engineering Center, School of Civil and Environmental Engineering Georgia Institute of Technology, Atlanta, Georgia 30332-0355, USA', u'full_name': u'Efe Guney'}, {u'author_order': 2, u'affiliation': u'Computer Aided Structural Engineering Center, School of Civil and Environmental Engineering Georgia Institute of Technology, Atlanta, Georgia 30332-0355, USA', u'full_name': u'Kenneth Will'}] Tsinghua Science and Technology, 2008

A multifrontal code is introduced for the efficient solution of the linear system of equations arising from the analysis of structures. The factorization phase is reduced into a series of interleaved element assembly and dense matrix operations for which the BLAS3 kernels are used. A similar approach is generalized for the forward and back substitution phases for the efficient solution ...

Blind source separation by simultaneous third-order tensor diagonalization

[{u'author_order': 1, u'affiliation': u'K.U. Leuven - E.E. Dept.- ESAT - SISTA, Kard. Mercierlaan 94, B-3001 Leuven (Heverlee), Belgium', u'full_name': u'Lieven De Lathauwer'}, {u'author_order': 2, u'affiliation': u'K.U. Leuven - E.E. Dept.- ESAT - SISTA, Kard. Mercierlaan 94, B-3001 Leuven (Heverlee), Belgium', u'full_name': u'Bart De Moor'}, {u'author_order': 3, u'affiliation': u'K.U. Leuven - E.E. Dept.- ESAT - SISTA, Kard. Mercierlaan 94, B-3001 Leuven (Heverlee), Belgium', u'full_name': u'Joos Vandewalle'}] 1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

We develop a technique for Blind Source Separation based on simultaneous diagonalization of (linear combinations of) third-order tensor "slices" of the fourth-order cumulant. It will be shown that, in a Jacobi-type iteration scheme, the computation of an elementary rotation can be reformulated in terms of a simultaneous matrix diagonalization.

Bad data processing when using the coupled measurement model and Takahashi's sparse inverse method

[{u'author_order': 1, u'affiliation': u'Northeastern University, Boston, MA, USA', u'authorUrl': u'', u'full_name': u'Bulent Bilir', u'id': 38228763800}, {u'author_order': 2, u'affiliation': u'Northeastern University, Boston, MA, USA', u'authorUrl': u'', u'full_name': u'Ali Abur', u'id': 37272386300}] IEEE PES Innovative Smart Grid Technologies, Europe, 2014

The paper revisits the computation of residual covariance matrix diagonal entries, which are used for calculating the normalized residuals that are in turn used for bad data identification. It is shown that these entries may be inadvertently computed incorrectly if one uses the commonly accepted implementation of the sparse inverse method due to the numerical cancellations that occur in the ...

A method for computing the information matrix of stationary Gaussian processes

[{u'author_order': 1, u'affiliation': u'Institute\xbb de Telecomunica\xe7\xf5es and D.E.E.C., Institute\xb7 Superior T\xe9cnico', u'full_name': u'Jos\xe9 M. B. Dias'}, {u'author_order': 2, u'affiliation': u'Institute\xbb de Telecomunica\xe7\xf5es and D.E.E.C., Institute\xb7 Superior T\xe9cnico', u'full_name': u'Jos\xe9 M. N. Leit\xe3o'}] 1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

This paper proposes a new method for the efficient computation of the Fisher information matrix of zero-mean complex stationary Gaussian processes. Its complexity (measured by the number of floating point operations) is smaller than the fastest previously available procedure. The key idea exploited is that the Fisher information matrix depends only on the sum of the diagonals of the inverse ...

A method to compute reactive power margins with respect to v

[{u'author_order': 1, u'full_name': u'T.V. Cutsem'}] IEEE Power Engineering Review, 1991


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Educational Resources on Matrices

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  • Symmetrical Components Using Matrix Methods

    The method of symmetrical components has been an important tool for the study of unbalanced three‐phase systems, unsymmetrical short‐circuit currents, models of rotating machines and transmission lines, etc. This chapter studies three‐phase balanced systems, by considering these as single‐phase system. The simplicity of representing a three‐phase as a single phase system is lost for unbalanced systems. There have been two approaches for the study of symmetrical components: A physical description, without going into much mathematical matrix algebra equations. The mathematical approach is adopted in this chapter. Symmetrical component method is a transform. There are three steps that are applicable in any transform for the solution of a problem. The matrix theory can be applied to understand some fundamental aspects of symmetrical components. The chapter also discusses the similarity transformation, symmetrical component transformation, and Clarke component transformation. The significance of symmetrical components is illustrated with an example.

  • Appendix C: Matrix Multiplication

  • Multiple‐Beam Antennas

    This chapter contains sections titled:IntroductionBeamformersLow Sidelobes and Beam InterpolationBeam OrthogonalityAcknowledgmentsReferences

  • Antenna Management

    This chapter contains sections titled: * Capacity of MIMO Channels * MIMO Transmission * Multiuser MIMO ]]>

  • Kalman Filter‐based Approaches for Positioning: Integrating Global Positioning with Inertial Sensors

    The Kalman filter (KF) theory is a fundamental milestone in signal processing and automatic control. This chapter discusses the main techniques related to Kalman filtering for satellite navigation. In particular, It explains the structure of the KF exploited in a global navigation satellite system (GNSS) receiver to compute the position of the user and to integrate the standard GNSS receiver with an inertial navigation system (INS). The chapter shows how KF is used in a standalone GNSS receiver to compute the classic position‐velocity‐time (PVT) solution. It provides some fundamentals of inertial navigation and discusses the characterization of the inertial sensors in terms of deterministic and stocastic noises, calibration, and alignment as fundamental prerequisites for any fruitful integration process. The three classic GNSS‐INS integration principles are presented, namely the so‐called loosely integrated, tightly integrated, and ultra‐tightly integrated architectures. Finally, the results of a live vehicular test campaign to compare two such implementations are shown and discussed.

  • Approaches to High-Dimensional Covariance and Precision Matrix Estimations

    This chapter introduces several recent developments for estimating large covariance and precision matrices without assuming the covariance matrix to be sparse. It explains two methods for covariance estimation: namely covariance estimation via factor analysis, and precision Matrix Estimation and Graphical Models. The low rank plus sparse representation holds on the population covariance matrix. The chapter presents several applications of these methods, including graph estimation for gene expression data, and several financial applications. It then shows how estimating covariance matrices of high- dimensional asset excess returns play a central role in applications of portfolio allocations and in risk management. The chapter explains the factor pricing model, which is one of the most fundamental results in finance. It elucidates estimating risks of large portfolios and large panel test of factor pricing models. The chapter illustrates the recent developments of efficient estimations in panel data models.

  • Autonomous Learning and New Possibilities for Intercultural Communication in Online Higher Education in Mexico

    This chapter examines the role of autonomous learning among students and teachers mediated by information and communication technologies (ICTs) in building meaningful curricular experiences, and creating bridges between curricular and didactic development, reflective thinking and learning practices. In undertaking such analysis, the author draws on experiences from online courses that are part of distinct degree programs at the University of Guadalajara in Mexico. The chapter affirms that educators and students using autonomous learning, based on curricular experiences, can improve pedagogical and communicational interactions for a meaningful construction of knowledge in higher education, particularly when such experiences are extended into intercultural global contexts (e.g., students located in different nations using ICTs to participate in the same online class). The chapter offers a critical analysis of how autonomous learning can transform the use of ICTs and facilitate the development of more complex, diverse, inclusive and wider learning and teaching environments.

  • Multivariate Analysis

    Multivariate analysis deals with situations in which several variables are measured on each experimental unit. In most cases of interest it is known or assumed that some form of relationship exists among the variables, and hence that considering each of them separately would entail a loss of information. Some possible goals of the analysis are: reduction of dimensionality, identification, and explanatory models. This chapter explores the need for robust substitutes for the mean vector and covariance matrix. The substitutes are generally referred to as multivariate location vectors and scatter matrices. Affine equivariance is a desirable property of an estimator. In order to increase the efficiency of a given estimator one‐step reweighting procedure can be used. The chapter presents a family of estimators with controllable efficiency based on the same principle as the regression MM‐estimators.

  • Classical Detection

    This chapter contains sections titled:Formalism of Quantum InformationHypothesis Detection for Collaborative SensingSample Covariance MatrixRandom Matrices with Independent RowsThe Multivariate Normal DistributionSample Covariance Matrix Estimation and Matrix Compressed SensingLikelihood Ratio Test

  • Acknowledgments

    I am very grateful to all those who have contributed to this book in various ways. I owe special thanks to Bjarki Valtysson, Frederik Tygstrup, and Peter Duelund, for their supervision and help thinking through this project, its questions, and its forms. I also wish to thank Andrew Prescott, Tobias Olsson, and Rune Gade for making my dissertation defense a memorable and thoroughly enjoyable day of constructive critique and lively discussions. Important parts of the research for this book further took place during three visiting stays at Cornell University, Duke University, and Columbia University. I am very grateful to N. Katherine Hayles, Andreas Huyssen, Timothy Brennan, Lydia Goehr, Rodney Benson, and Fredric Jameson, who generously welcomed me across the Atlantic and provided me with invaluable new perspectives, as well as theoretical insights and challenges. Beyond the aforementioned, three people in particular have been instrumental in terms of reading through drafts and in providing constructive challenges, intellectual critique, moral support, and fun times in equal proportions—thank you so much Kristin Veel, Henriette Steiner, and Daniela Agostinho. Marianne Ping-Huang has further offered invaluable support to this project and her theoretical and practical engagement with digital archives and academic infrastructures continues to be a source of inspiration. I am also immensely grateful to all the people working on or with mass digitization who generously volunteered their time to share with me their visions for, and perspectives on, mass digitization.

Standards related to Matrices

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