Libros sobre el tema "Linear quadratic theory"

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1

Sima, Vasile. Algorithms for linear-quadratic optimization. New York: M. Dekker, 1996.

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2

Anderson, Brian D. O. Optimal control: Linear quadratic methods. Englewood Cliffs, N.J: Prentice Hall, 1990.

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3

Quadratic forms, linear algebraic groups, and cohomology. New York: Springer, 2010.

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4

Introduction to quadratic forms. Berlin: Springer, 2000.

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5

1964-, Hartley T. T. y Chicatelli S. P. 1964-, eds. The hyperbolic map and applications to the linear quadratic regulator. New York: Springer-Verlag, 1989.

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6

1955-, Mehrmann V. L., ed. The Autonomous linear quadratic control problem: Theory and numerical solution. Berlin: Springer-Verlag, 1991.

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7

Daiuto, Brian J. The Hyperbolic Map and Applications to the Linear Quadratic Regulator. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989.

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8

service), SpringerLink (Online, ed. Mono- and Multivariable Control and Estimation: Linear, Quadratic and LMI Methods. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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9

Arithmetic and analytic theories of quadratic forms and Clifford groups. Providence, R.I: American Mathematical Society, 2004.

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10

Roche, Maurice J. Some linear-quadratic solution methods to stochastic nonlinear rational expectations models. Maynooth, Co Kildare: Maynooth College, Department of Economics, 1994.

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11

Roche, Maurice J. Some linear-quadratic solution methods to stochastic nonlinear rational expectations models. Maynooth, Co Kildare: Maynooth College, Department of Economics, 1994.

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12

Sun, Jingrui y Jiongmin Yong. Stochastic Linear-Quadratic Optimal Control Theory: Differential Games and Mean-Field Problems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48306-7.

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13

Sun, Jingrui y Jiongmin Yong. Stochastic Linear-Quadratic Optimal Control Theory: Open-Loop and Closed-Loop Solutions. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-20922-3.

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14

C, Sprott Julien y ebrary Inc, eds. 2-D quadratic maps and 3-D ODE systems: A rigorous approach. Singapore: World Scientific Pub. Co., 2010.

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15

Rosen, I. Gary. On the continuous dependence with respect to sampling of the linear quadratic regulator problem for distributed parameter systems. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.

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16

1934-, Craig Roy R. y Lyndon B. Johnson Space Center., eds. A decentralized linear quadratic control design method for flexible structures: Interim report. Austin, Texas: Center for Aeromechanics Research, University of Texas at Austin, 1990.

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17

1957-, Adamian Armen y Langley Research Center, eds. Approximation theory for LQG optimal control of flexible structures. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1988.

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18

service), SpringerLink (Online, ed. Linear-Quadratic Controls in Risk-Averse Decision Making: Performance-Measure Statistics and Control Decision Optimization. New York, NY: Springer New York, 2013.

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19

International Workshop on Diophantine Methods, Lattices, and Arithmetic Theory of Quadratic Forms (2011 Banff, Alta.). Diophantine methods, lattices, and arithmetic theory of quadratic forms: International workshop, Banff International Research Station, November 13-18, 2011, Banff, Alberta, Canada. Editado por Chan, Wai Kiu, 1967- editor of compilation, Fukshansky, Lenny, 1973- editor of compilation, Schulze-Pillot, Rainer, editor of compilation y Vaaler, Jeffrey D., editor of compilation. Providence, Rhode Island: American Mathematical Society, 2013.

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20

Fujikoshi, Yasunori. Asymptotic approximations for EPMC's of the linear and the quadratic discriminant functions when the sample sizes and the dimension are large. Toronto: University of Toronto, Dept. of Statistics, 1997.

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21

Massachusetts Institute of Technology. Space Systems Laboratory. y United States. National Aeronautics and Space Administration., eds. H2 fixed architecture control design for large scale systems. Cambridge, MA: Space Systems Laboratory, Dept. of Aeronautics and Astronautics, Massachusetts Institute of Technology, 1990.

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22

1932-, Bass Hyman y Lam, T. Y. (Tsit-Yuen), 1942-, eds. Algebra. Providence, R.I: American Mathematical Society, 2010.

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23

1957-, Bonnans J. F., ed. Numerical optimization: Theoretical and practical aspects. Berlin: Springer, 2003.

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24

Ninul, Anatolij Sergeevič. Tenzornaja trigonometrija: Teorija i prilozenija / Theory and Applications /. Moscow, Russia: Mir Publisher, 2004.

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25

International Conference on p-Adic Functional Analysis (11th 2010 Université Blaise Pascal). Advances in non-Archimedean analysis: Eleventh International Conference on p-Adic Functional Analysis, July 5-9 2010, Université Blaise Pascal, Clermont-Ferrand, France. Editado por Araujo-Gomez Jesus 1965-, Diarra B. (Bertin) 1944- y Escassut Alain. Providence, R.I: American Mathematical Society, 2011.

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26

Alladi, Krishnaswami, Frank Garvan y Ae Ja Yee. Ramanujan 125: International conference to commemorate the 125th anniversary of Ramanujan's birth, Ramanujan 125, November 5--7, 2012, University of Florida, Gainesville, Florida. Providence, Rhode Island: American Mathematical Society, 2014.

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27

Ninul, Anatolij Sergeevič. Tensor Trigonometry. Moscow, Russia: Fizmatlit Publisher, 2021.

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28

Anderson, Brian D. O. y John B. Moore. Optimal Control: Linear Quadratic Methods. Dover Publications, 2013.

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29

Anderson, Brian D. O. y John B. Moore. Optimal Control: Linear Quadratic Methods. Dover Publications, Incorporated, 2014.

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30

Linear Quadratic Control: An Introduction. Krieger Pub Co, 2000.

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31

JACOBSON, David H. Extensions of Linear-Quadratic Control, Optimization and Matrix Theory. Elsevier Science & Technology Books, 2000.

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32

Anderson, Brian D. O. y John B. Moore. Optimal Control: Linear Quadratic Methods (Dover Books on Engineering). Dover Publications, 2007.

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33

Raines, Allen Crawford. Hamiltonian-symplectic methods for solving the quadratic regulator problem. 1993.

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34

Ostertag, Eric. Mono- and Multivariable Control and Estimation: Linear, Quadratic and LMI Methods. Springer, 2013.

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35

Bellman, Richard. Introduction to the Mathematical Theory of Control Processes: Linear Equations and Quadratic Criteria. Elsevier Science & Technology Books, 2016.

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36

Yong, Jiongmin y Jingrui Sun. Stochastic Linear-Quadratic Optimal Control Theory: Differential Games and Mean-Field Problems. Springer, 2020.

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37

Yong, Jiongmin y Jingrui Sun. Stochastic Linear-Quadratic Optimal Control Theory : Open-Loop and Closed-Loop Solutions: Volume 1. Springer, 2020.

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38

An LQR controller design approach for a large gap magnetic suspension system (LGMSS). Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.

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39

Mehrmann, V. L. The Autonomous Linear Quadratic Control Problem: Theory and Numerical Solution (Lecture Notes in Control and Information Sciences). Springer, 1991.

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40

Pham, Khanh D. Linear-Quadratic Controls in Risk-Averse Decision Making: Performance-Measure Statistics and Control Decision Optimization. Springer, 2012.

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41

The Autonomous Linear Quadratic Control Problem: Theory and Numerical Solution (Lecture Notes in Control and Information Sciences). Springer, 1991.

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42

Linearquadratic Controls In Riskaverse Decision Making Performancemeasure Statistics And Control Decision Optimization. Springer, 2012.

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43

Deruelle, Nathalie y Jean-Philippe Uzan. Gravitational radiation. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198786399.003.0054.

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This chapter attempts to calculate the radiated energy of a source in the linear approximation of general relativity to infinity in the lowest order. For this, the chapter first expands the Einstein equations to quadratic order in metric perturbations. It reveals that the radiated energy is then given by the (second) quadrupole formula, which is the gravitational analog of the dipole formula in Maxwell theory. This formula is a priori valid only if the motion of the source is due to forces other than gravity. Finally, this chapter shows that, to prove this formula for the case of self-gravitating systems, the Einstein equations to quadratic order must be solved, and the radiative field in the post-linear approximation of general relativity obtained.
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44

Bonnans, J. Frédéric, Jean Charles Gilbert, Claude Lemaréchal y Claudia A. Sagastizábal. Numerical Optimization: Theoretical and Practical Aspects. Springer, 2003.

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45

Sayed, Ali H., Thomas Kailath y Babak Hassibi. Linear Estimation. Prentice Hall, 2000.

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46

Sayed, Ali H., Thomas Kailath y Babak Hassibi. Linear Estimation. Prentice Hall, 2000.

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47

Caraballo Carmona, Carlos Manuel y Francisco Lázaro García Fernández. Methodology of Mathematics Teaching. Treatment to School Mathematics Equations. Editorial Tecnocientífica Americana, 2021. http://dx.doi.org/10.51736/eta2021edu1.

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This book is aimed at pre-university students and its purpose is to contribute to the development of their knowledge related to the algebraic and transcendent equations studied at school, as well as their application to different situations that occur in practice in an innovative and creative way, using the procedures for solving them, so that it allows the consolidation of attitudes such as industriousness, responsibility and science. The system of knowledge worked on and treated didactically in this book is related to the algebraic equations and within them the linear, quadratic, fractional and radical equations, the modular equations and the transcendental equations such as, the exponential, logarithmic and trigonometric equations, providing the minimum theoretical and methodological resources, necessary to learn and to successfully face the exercises and problems proposed in each chapter.
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