Linear estimation and stochastic control / M. H. A. Davis.
Series Chapman and Hall mathematics seriesEditor: London : New York : Chapman and Hall ; Wiley : distributed in the U.S.A. by Halsted Press, 1977Descripción: xii, 224 p. : ill. ; 23 cmISBN: 0470992158Tema(s): Stochastic control theory | Estimation theoryOtra clasificación: *CODIGO*Preface page vii -- Abbreviations and Notation vii -- 1 Finite-dimensional linear estimation I -- 1.1 The geometrical structure of linear estimation [1] -- 1.2 Problems anti complements [11] -- 2 Stochastic processes and linear estimation [13] -- 2.1 Stochastic processes [14] -- 2.2 Hilbert space [30] -- 2.3 Spaces of square-mtcgrablc random variables [42] -- 2.4 Problems and complements [54] -- 3 Orthogonal increments processes [56] -- 3.1 General properties [56] -- 3.2 Counting processes [59] -- 33 Brownian motion and white noise [71] -- 3.4 Wiener integrals [84] -- 3.5 Problems and complements [96] -- 4 Estimation in dynamical systems [100] -- 4.1 Multidimensional processes [102] -- 4.2 Linear stochastic equations [104] -- 4.3 The Innovations Process [117] -- 4.4 The Kalman Filter [134] -- 4.5Problems and complements [148] -- 5 Linear stochastic control [151] -- 5.1 Dynamic programming and the deterministic linear regulator [157] -- 5.2 The stochastic linear regulator [163] -- 5.3 Partial observations and the Separation Principle173 -- 5.4 Infinite-time problems [182] -- 5.5Problems and complements [190] -- 6 An outline of further developments [193] -- 6.1 Non-linear filtering and control [194] -- 6.2 Distributed*parameter systems [201] -- Appendix: Independence and Conditional Expectation [209] -- References [216] -- Index [219] --
| Item type | Home library | Shelving location | Call number | Materials specified | Status | Date due | Barcode |
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Libros
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Instituto de Matemática, CONICET-UNS | Libros ordenados por tema | 60 D261 (Browse shelf) | Available | A-9355 |
Includes index.
Bibliografía: p. 216-218.
Preface page vii --
Abbreviations and Notation vii --
1 Finite-dimensional linear estimation I --
1.1 The geometrical structure of linear estimation [1] --
1.2 Problems anti complements [11] --
2 Stochastic processes and linear estimation [13] --
2.1 Stochastic processes [14] --
2.2 Hilbert space [30] --
2.3 Spaces of square-mtcgrablc random variables [42] --
2.4 Problems and complements [54] --
3 Orthogonal increments processes [56] --
3.1 General properties [56] --
3.2 Counting processes [59] --
33 Brownian motion and white noise [71] --
3.4 Wiener integrals [84] --
3.5 Problems and complements [96] --
4 Estimation in dynamical systems [100] --
4.1 Multidimensional processes [102] --
4.2 Linear stochastic equations [104] --
4.3 The Innovations Process [117] --
4.4 The Kalman Filter [134] --
4.5Problems and complements [148] --
5 Linear stochastic control [151] --
5.1 Dynamic programming and the deterministic linear regulator [157] --
5.2 The stochastic linear regulator [163] --
5.3 Partial observations and the Separation Principle173 --
5.4 Infinite-time problems [182] --
5.5Problems and complements [190] --
6 An outline of further developments [193] --
6.1 Non-linear filtering and control [194] --
6.2 Distributed*parameter systems [201] --
Appendix: Independence and Conditional Expectation [209] --
References [216] --
Index [219] --
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