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

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

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

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

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

IEEE Power Engineering Review, 1991

None


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Educational Resources on Matrices

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IEEE-USA E-Books

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

    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 of structures having multiple load conditions. The program performs all assembly and solution steps in parallel. Examples are presented which demonstrate the code's performance on single and dual core processor computers.

  • Blind source separation by simultaneous third-order tensor diagonalization

    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

    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 formation of the so-called gain matrix. This situation occurs when the coupled measurement model is used. Indeed, the coupled model is required if there are current measurements that do not lend themselves to decoupling. Numerical example will be given for a test power system to show the impact of these cancellations on bad data analysis that uses post- processing of residuals and the largest normalized residual test. The errors may lead to sequential removal of good data eventually leading to a biased estimation. They may also lead to unacceptable covariance values, e.g., less than zero, which will then destroy the validity of bad data analysis. While it appears like a minor oversight in the application of efficient sparse inverse implementation, due to its adverse impact on state estimation and therefore overall power system operation, it will have to be corrected. The paper will first illustrate the issue and then a simple modification in the implementation of the sparse inverse method will be shown in order to avoid this error.

  • A method for computing the information matrix of stationary Gaussian processes

    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 covariance matrix derivative (with respect to the model parameters), rather than on the whole matrix. To obtain the referred sum, a new efficient technique, built upon the Trench algorithm for computing the inverse of a Toeplitz matrix, is presented.

  • A method to compute reactive power margins with respect to v

    None

  • A simple method to determine observable islands for state estimation

    This paper presents a numerical method which makes use of the triangular factors of a singular gain matrix in order to determine the observable islands for a given set of measurements. The proposed method can accomplish this task in a noniterative manner by way of sparse triangular factorization and back substitution only. Numerical examples demonstrating the application of the proposed method to typical power systems are also included.

  • Complexity and search space reduction in cyclic-by-row PEVD algorithms

    In recent years, several algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is a generalisation of the ordinary EVD and uses paraunitary operations to diagonalise a parahermitian matrix. This paper addresses potential computational savings that can be applied to existing cyclic-by-row approaches for the PEVD. These savings are found during the search and rotation stages, and do not significantly impact on algorithm accuracy. We demonstrate that with the proposed techniques, computations can be significantly reduced. The benefits of this are important for a number of broadband multichannel problems.

  • Parallel matrix inversion techniques

    In this paper, we present techniques for inverting sparse, symmetric and positive definite matrices on parallel and distributed computers. We propose two algorithms, one for SIMD implementation and the other for MIMD implementation. These algorithms are modified versions of Gaussian elimination and they take into account the sparseness of the matrix. Our algorithms perform better than the general parallel Gaussian elimination algorithm. In order to demonstrate the usefulness of our technique, we implemented the snake problem using our sparse matrix algorithm. Our studies reveal that the proposed sparse matrix inversion algorithm significantly reduces the time taken for obtaining the solution of the snake problem. In this paper, we present the results of our experimental work.

  • A network application package with a centralized topology engine

    The efficiency of sparse matrix and vector methods in calculating the state of electrical networks is beyond dispute. Kussel et al. (1996) have shown that extended use of sparse matrix methods sets new standards of efficiency in determining the topological state of an electrical network. Due to the fact that the main data structure used by the new topology method already contains all items to build up the Jacobean, the complete sequence of an online network calculation like load flow or state estimation has been abridged drastically. Such methods are capable of updating network data structures and performing a load flow calculation even for large EMS, very large DMS-networks or a mix of both in a few seconds. On this basis the authors have developed a network application package with a centralized topology engine which has been implemented in an advanced DMS system.

  • Mining Binary Data with Matrix Algebra

    Many applications such as intelligent tutoring system (ITS) use data that are better represented as binary data. This paper presents a novel algorithm called MBER (Mining Binary Data Efficiently by Reduced AND operations) for finding frequent itemsets in a binary dataset using matrix algebra operations. Frequent itemsets are sets of items in a transactional database that occur together frequently (defined by a user-given threshold value called minimum support). Existing algorithms that operate on binary data, such as ABBM, generate frequent itemsets by performing exhaustive AND operations using brute force method. MBER, on the other hand, generates frequent itemsets using a novel technique in which it first uses matrix algebra operations to find those transactions that have m common items in them (called as potential transactions) and then performs AND operations on only such potential transactions. This reduces the total number of AND operations required considerably (by less than a quarter) and thereby improves the efficiency of the algorithm. MBER also shows a significant improvement over traditional algorithms that generate frequent itemsets, such as Apriori, by eliminating the need to (i) scan the database more than once and (ii) to generate large number of candidate itemsets. This paper concludes by a proof of correctness of MBER and a discussion on evaluating it.



Standards related to Matrices

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