Linear algebra
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IEEE Organizations related to Linear algebra
Back to TopConferences related to Linear algebra
Back to Top2014 American Control Conference  ACC 2014
All areas of the theory and practice of automatic control, including but not limited to network control systems, model predictive control, systems analysis in biology and medicine, hybrid and switched systems, aerospace systems, power and energy systems and control of nano and microsystems.
2010 IEEE 51st Annual Symposium on Foundations of Computer Science (FOCS)
The 51st Annual Symposium on Foundations of Computer Science (FOCS2010), sponsored by the IEEE Computer Society Technical Committee on Mathematical Foundations of Computing, will be held at the Monte Carlo Hotel in Las Vegas, Nevada, October 2426, 2010. A series of tutorial presentations will be given on October 23. Papers presenting new and original research on the theory of computation are sought, including papers that broaden the reach of computer science theory, or raise important problems that can ben
Periodicals related to Linear algebra
Back to TopAutomatic 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 ...
Computers, IEEE Transactions on
Design and analysis of algorithms, computer systems, and digital networks; methods for specifying, measuring, and modeling the performance of computers and computer systems; design of computer components, such as arithmetic units, data storage devices, and interface devices; design of reliable and testable digital devices and systems; computer networks and distributed computer systems; new computer organizations and architectures; applications of VLSI ...
The most highlycited general interest journal in electrical engineering and computer science, the Proceedings is the best way to stay informed on an exemplary range of topics. This journal also holds the distinction of having the longest useful archival life of any EE or computer related journal in the world! Since 1913, the Proceedings of the IEEE has been the ...
Quantum Electronics, IEEE Journal of
Generation, amplification, modulation, detection, waveguiding, or techniques and effects that can affect the propagation characteristics of coherent electromagnetic radiation having submillimeter and shorter wavelengths
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
Integrated circuits and systems;VLSI based Architecture and applications; highspeed circuits and interconnect; mixedsignal SoC; speed/area/power/noise tradeoffs in CMOS circuits.
Xplore Articles related to Linear algebra
Back to TopGeneralized Encoding and Decoding Operators for LatticeBased Associative Memories
John McElroy; Paul Gader IEEE Transactions on Neural Networks, 2009
During the 1990s, Ritter introduced a new family of associative memories based on lattice algebra instead of linear algebra. These memories provide unlimited storage capacity, unlike linearcorrelationbased models. The canonical latticebased memories, however, are susceptible to noise in the initial input data. In this brief, we present novel methods of encoding and decoding latticebased memories using two families of ordered ...
Sensitivity analysis of the feedback synthesis problem
M. M. Konstantinov; P. H. Petkov; N. D. Christov IEEE Transactions on Automatic Control, 1997
Sensitivity analysis of the feedback synthesis problem (FSP) for linear multivariable systems is presented. Both local linear and nonlocal nonlinear perturbation bounds are derived using the Schur form of the closedloop state matrix. Condition numbers for the general FSP and the pole assignment problem in particular are given. Restrictions are imposed only on the degrees of the invariant polynomials of ...
Visual Explanation of Mathematics in Latent Semantic Analysis
Yukari Shirota; Basabi Chakraborty 2015 IIAI 4th International Congress on Advanced Applied Informatics, 2015
Latent Semantic Analysis (LSA) is a widely used method in text mining fields to extract the latent concept. The mathematical technique behind LSA is Singular Value Decomposition (SVD) in which the key concept is the eigen values. It is difficult to understand the underlying mathematics for general people, not proficient in mathematics. One reason might be that the linear algebra ...
Comments on "Equivalent representation of lossy transmission lines&#8212;Part I"
C. T. Tai; K. R. Shah; Y. Yavin Proceedings of the IEEE, 1972
None
Cad for minimal order compensators
S. Gutman Proceedings. ICCON IEEE International Conference on Control and Applications, 1989
First Page of the Article ![](/xploreAssets/images/absImages/00770666.png)
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Educational Resources on Linear algebra
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Generalized Encoding and Decoding Operators for LatticeBased Associative Memories
John McElroy; Paul Gader IEEE Transactions on Neural Networks, 2009
During the 1990s, Ritter introduced a new family of associative memories based on lattice algebra instead of linear algebra. These memories provide unlimited storage capacity, unlike linearcorrelationbased models. The canonical latticebased memories, however, are susceptible to noise in the initial input data. In this brief, we present novel methods of encoding and decoding latticebased memories using two families of ordered ...
Sensitivity analysis of the feedback synthesis problem
M. M. Konstantinov; P. H. Petkov; N. D. Christov IEEE Transactions on Automatic Control, 1997
Sensitivity analysis of the feedback synthesis problem (FSP) for linear multivariable systems is presented. Both local linear and nonlocal nonlinear perturbation bounds are derived using the Schur form of the closedloop state matrix. Condition numbers for the general FSP and the pole assignment problem in particular are given. Restrictions are imposed only on the degrees of the invariant polynomials of ...
Visual Explanation of Mathematics in Latent Semantic Analysis
Yukari Shirota; Basabi Chakraborty 2015 IIAI 4th International Congress on Advanced Applied Informatics, 2015
Latent Semantic Analysis (LSA) is a widely used method in text mining fields to extract the latent concept. The mathematical technique behind LSA is Singular Value Decomposition (SVD) in which the key concept is the eigen values. It is difficult to understand the underlying mathematics for general people, not proficient in mathematics. One reason might be that the linear algebra ...
Comments on "Equivalent representation of lossy transmission lines&#8212;Part I"
C. T. Tai; K. R. Shah; Y. Yavin Proceedings of the IEEE, 1972
None
Cad for minimal order compensators
S. Gutman Proceedings. ICCON IEEE International Conference on Control and Applications, 1989
First Page of the Article ![](/xploreAssets/images/absImages/00770666.png)
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IEEEUSA EBooks

This chapter contains sections titled: 9.1 The Algorithm, 9.2 The Analysis, 9.3 Problems, 9.4 Summary and Notes

This chapter contains sections titled: 10.1 The Algorithm, 10.2 The Analysis, 10.3 Problems, 10.4 Summary and Notes

In recent years, the life sciences have embraced simulation as an important tool in biomedical research. Engineers are also using simulation as a powerful step in the design process. In both arenas, Matlab has become the gold standard. It is easy to learn, flexible, and has a large and growing userbase. MATLAB for Engineering and the Life Sciences is a selfguided tour of the basic functionality of MATLAB along with the functions that are most commonly used in biomedical engineering and other life sciences. Although the text is written for undergraduates, graduate students and academics, those in industry may also find value in learning MATLAB through biologically inspired examples. For instructors, the book is intended to take the emphasis off of learning syntax so that the course can focus more on algorithmic thinking. Although it is not assumed that the reader has taken differential equations or a linear algebra class, there are short introductions to many of these concepts. Follow ng a short history of computing, the MATLAB environment is introduced. Next, vectors and matrices are discussed, followed by matrixvector operations. The core programming elements of MATLAB are introduced in three successive chapters on scripts, loops, and conditional logic. The last three chapters outline how to manage the input and output of data, create professional quality graphics and find and use Matlab toolboxes. Throughout, biomedical examples are used to illustrate MATLAB's capabilities. Table of Contents: Introduction / Matlab Programming Environment / Vectors / Matrices / Matrix  Vector Operations / Scripts and Functions / Loops / Conditional Logic / Data In, Data Out / Graphics / Toolboxes

A Parallel Linear Algebra Library for the Denelcor HEP
This chapter contains sections titled: Introduction, Algorithms Based on Modules, Structure of the Algorithms, Efficient Modules for the Denelcor REP, Library Issues, Performance, Acknowledgements, References

An Introduction to Linear Algebra in Parallel Distributed Processing
This chapter contains sections titled: Vectors, Matrices and Linear Systems, Matrices, Nonlinear Systems

This chapter contains sections titled: 11.1 Strategy, 11.2 Good Numbers, 11.3 Quantum Part of the Algorithm, 11.4 Analysis of the Quantum Part, 11.5 Probability of a Good Number, 11.6 Using a Good Number, 11.7 Continued Fractions, 11.8 Problems, 11.9 Summary and Notes

Foundations of Robotics presents the fundamental concepts and methodologies for the analysis, design, and control of robot manipulators. It explains the physical meaning of the concepts and equations used, and it provides, in an intuitively clear way, the necessary background in kinetics, linear algebra, and control theory. Illustrative examples appear throughout.The author begins by discussing typical robot manipulator mechanisms and their controllers. He then devotes three chapters to the analysis of robot manipulator mechanisms. He covers the kinematics of robot manipulators, describing the motion of manipulator links and objects related to manipulation. A chapter on dynamics includes the derivation of the dynamic equations of motion, their use for control and simulation and the identification of inertial parameters. The final chapter develops the concept of manipulability.The second half focuses on the control of robot manipulators. Various positioncontrol algorithms that guide the manipulator's end effector along a desired trajectory are described Two typical methods used to control the contact force between the end effector and its environments are detailed For manipulators with redundant degrees of freedom, a technique to develop control algorithms for active utilization of the redundancy is described. Appendixes give compact reviews of the function atan2, pseudo inverses, singularvalue decomposition, and Lyapunov stability theory.Tsuneo Yoshikawa teaches in the Division of Applied Systems Science in Kyoto University's Faculty of Engineering.

Realtime adaptive informationtheoretic optimization of neurophysiology experiments
Adaptively optimizing experiments can significantly reduce the number of trials needed to characterize neural responses using parametric statistical models. However, the potential for these methods has been limited to date by severe computational challenges: choosing the stimulus which will provide the most information about the (typically highdimensional) model parameters requires evaluating a highdimensional integration and optimization in near real time. Here we present a fast algorithm for choosing the optimal (most informative) stimulus based on a Fisher approximation of the Shannon information and specialized numerical linear algebra techniques. This algorithm requires only lowrank matrix manipulations and a onedimensional linesearch to choose the stimulus and is therefore efficient even for high dimensional stimulus and parameter spaces; for example, we require just 15 milliseconds on a desktop computer to optimize a 100dimensional stimulus. Our algorithm therefore makes realtime adaptive experimental design feasible. Simulation results show that model parameters can be estimated much more efficiently using these adaptive techniques than by using random (nonadaptive) stimuli. Finally, we generalize the algorithm to efficiently handle both fast adaptation due to spikehistory effects and slow, nonsystematic drifts in the model parameters.

Boolean Functions, Quantum Bits, and Feasibility
This chapter contains sections titled: 4.1 Feasible Boolean Functions, 4.2 An Example, 4.3 Quantum Representation of Boolean Arguments, 4.4 Quantum Feasibility, 4.5 Problems, 4.6 Summary and Notes

Linear complementarity problems (LCPs) have for many years been used in physicsbased animation to model contact forces between rigid bodies in contact. More recently, LCPs have found their way into the realm of fluid dynamics. Here, LCPs are used to model boundary conditions with fluidwall contacts. LCPs have also started to appear in deformable models and granular simulations. There is an increasing need for numerical methods to solve the resulting LCPs with all these new applications. This book provides a numerical foundation for such methods, especially suited for use in computer graphics. This book is mainly intended for a researcher/Ph.D. student/postdoc/professor who wants to study the algorithms and do more work/research in this area. Programmers might have to invest some time brushing up on math skills, for this we refer to Appendices A and B. The reader should be familiar with linear algebra and differential calculus. We provide pseudo code for all the numerical methods, w ich should be comprehensible by any computer scientist with rudimentary programming skills. The reader can find an online supplementary code repository, containing Matlab implementations of many of the core methods covered in these notes, as well as a few Python implementations [Erleben, 2011].
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Guidance Navigation and Control Engineer / Orlando, Florida
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