| ISBN |
9783642968426 |
| 기타 표준번호 |
10.1007/978-3-642-96842-6 |
| 청구기호 |
QA268 |
| 형태사항 |
online resource.
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| 언어 |
English |
| 내용 |
1. Elements of Probability Theory -- 1.1 Probability and Probability Spaces -- 1.2 Random Variables and ?�Almost Sure??Properties -- 1.3 Random Vectors -- 1.4 Stochastic Processes -- 2. Calculus in Mean Square -- 2.1 Convergence in Mean Square -- 2.2 Continuity in Mean Square -- 2.3 Differentiability in Mean Square -- 2.4 Integration in Mean Square -- 2.5 Mean-Square Calculus of Random N Vectors -- 2.6 The Wiener-L챕vy Process -- 2.7 Mean-Square Calculus and Gaussian Distributions -- 2.8 Mean-Square Calculus and Sample Calculus -- 3. The Stochastic Dynamic System -- 3.1 System Description -- 3.2 Uniqueness and Existence of m.s. Solution to (3.3) -- 3.3 A Discussion of System Representation -- 4. The Kalman-Bucy Filter -- 4.1 Some Preliminaries -- 4.2 Some Aspects of L2 ([a, b]) -- 4.3 Mean-Square Integrals Continued -- 4.4 Least-Squares Approximation in Euclidean Space -- 4.5 A Representation of Elements of H (Z, t) -- 4.6 The Wiener-Hopf Equation -- 4.7 Kalman-Bucy Filter and the Riccati Equation -- 5. A Theorem by Liptser and Shiryayev -- 5.1 Discussion on Observation Noise -- 5.2 A Theorem of Liptser and Shiryayev -- Appendix: Solutions to Selected Exercises -- References.
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| 주제 |
Computer science.
Coding theory.
Probabilities.
Statistics.
Computer Science.
Coding and Information Theory.
Probability Theory and Stochastic Processes.
Statistics, general.
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| 보유판 및 특별호 저록 |
Springer eBooks
Printed edition: 9783642968440
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| QR CODE |
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