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1.

図書

図書
Masanao Aoki
出版情報: New York : Academic Press, 1967  xv, 354 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 32
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2.

図書

図書
Touraj Assefi
出版情報: New York : Wiley, c1979  xi, 291 p. ; 24 cm
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3.

図書

図書
Karl J. Åström
出版情報: New York : Academic Press, 1970  xi, 299 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 70
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目次情報: 続きを見る
Preface
Contents
Overview / 1:
Methods of Operator Approximation in System Modelling / I:
Nonlinear Operator Approximation with Preassigned Accuracy / 2:
Introduction / 2.1:
Generic formulation of the problem / 2.2:
Operator approximation in space C([0; 1]) / 2.3:
Operator approximation in Banach spaces by polynomial operators / 2.4:
Approximation on compact sets in topological vector spaces / 2.5:
Approximation on noncompact sets in Hilbert spaces / 2.6:
Special results for maps into Banach spaces / 2.7:
Concluding remarks / 2.8:
Interpolation of Nonlinear Operators 65 / 3:
Lagrange interpolation in Banach spaces / 3.1:
Weak interpolation of nonlinear operators / 3.3:
Some related results / 3.4:
Realistic Operators and their Approximation / 3.5:
Formalization of concepts related to description of real-world objects / 4.1:
Approximation of RÂícontinuous operators / 4.3:
Methods of Best Approximation for Nonlinear Operators / 4.4:
Best Approximation of nonlinear operators in Banach spaces: Deterministic case / 5.1:
Estimation of mean and covariance matrix for random vectors / 5.3:
Best Hadamard-quadratic approximation / 5.4:
Best polynomial approximation / 5.5:
Best causal approximation / 5.6:
Best hybrid approximations / 5.7:
Optimal Estimation of Random Vectors / 5.8:
Computational Methods for Optimal Filtering of Stochastic Signals / 6:
Optimal linear Filtering in Finite dimensional vector spaces / 6.1:
Optimal linear Filtering in Hilbert spaces / 6.3:
Optimal causal linear Filtering with piecewise constant memory / 6.4:
Optimal causal polynomial Filtering with arbitrarily variable memory / 6.5:
Optimal nonlinear Filtering with no memory constraint / 6.6:
Computational Methods for Optimal Compression and Reconstruction of Random Data / 6.7:
Standard Principal Component Analysis and Karhunen-Loeeve transform (PCA{KLT) / 7.1:
Rank-constrained matrix approximations / 7.3:
Generic PCA{KLT / 7.4:
Optimal hybrid transform based on Hadamard-quadratic approximation / 7.5:
Optimal transform formed by a combination of nonlinear operators / 7.6:
Optimal generalized hybrid transform / 7.7:
Bibliography / 7.8:
Index
Preface
Contents
Overview / 1:
4.

図書

図書
D.J. Bartholomew
出版情報: London ; New York : Wiley, 1973  xi, 411 p. ; 24 cm
シリーズ名: Wiley series in probability and mathematical statistics
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5.

図書

図書
By Alain Bensoussan and Jacques-louis Lioms
出版情報: Paris : Gauthier-Villars , Bristol : Hilger[m] , Paris : Bordas, c1984  xiv, 684 p ; 25 cm
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6.

図書

図書
U. Narayan Bhat
出版情報: New York : J. Wiley, c1972  xvi, 414 p. ; 23 cm
シリーズ名: Wiley series in probability and mathematical statistics
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目次情報: 続きを見る
Preface
Stochastic Processes: Description and Definition / 1:
Introduction / 1.1:
Description and Definition / 1.2:
Probability Distributions / 1.3:
The Markov Process / 1.4:
The Renewal Process / 1.5:
The Stationary Process / 1.6:
A Plan for the Remaining Chapters / 1.7:
References
Exercises
Elementary Review Exercises
Advanced Review Exercises
Markov Chains / 2:
The n-Step Transition Probability Matrix / 2.1:
Classification of States / 2.3:
A Canonical Representation of the Transition Probability Matrix / 2.4:
Classification of States in Practice / 2.5:
Finite Markov Chains with Transient States / 2.6:
Irreducible Markov Chains with Ergodic States / 3:
Transient Behavior / 3.1:
Limiting Behavior / 3.2:
First Passage and Related Results / 3.3:
Branching Processes and other Special Topics / 4:
Branching Processes / 4.1:
Markov Chains of Order Higher than 1 / 4.2:
Lumpable Markov Chains / 4.3:
Reversed Markov Chains / 4.4:
Statistical Inference for Markov Chains / 5:
Estimation of the Elements in a Transition Probability Matrix / 5.1:
Hypothesis Testing Issues for Markov Chains / 5.2:
Inference From Partially Observable Markov Chains / 5.3:
Statistical Inference for Branching Processes / 5.4:
Additional Comments / 5.5:
Applied Markov Chains / 6:
Queueing Models / 6.1:
Inventory Systems / 6.2:
Storage Models / 6.3:
Industrial Mobility of Labor / 6.4:
Educational Advancement / 6.5:
Human Resource Management / 6.6:
Term Structure / 6.7:
Income Determination under Uncertainty / 6.8:
A Markov Decision Process / 6.9:
Simple Markov Processes / 7:
Examples / 7.1:
Markov Processes: General Properties / 7.2:
The Poisson Process / 7.3:
The Pure Birth Process / 7.4:
The Pure Death Process / 7.5:
Birth and Death Processes / 7.6:
Limiting Distributions / 7.7:
Markovian Networks / 7.8:
Additional Examples / 7.9:
Statistical Inference for Simple Markov Processes / 8:
Estimation of Parameters / 8.1:
Hypothesis Testing for Simple Markov Processes / 8.2:
Statistical Inference for Queues / 8.3:
Applied Markov Processes / 8.4:
The Machine Interference Problem / 9.1:
Queueing Networks / 9.3:
Flexible Manufacturing Systems / 9.4:
Reliability Models / 9.5:
Markovian Combat Models / 9.7:
Stochastic Models for Social Networks / 9.8:
Recovery, Relapse, and Death Due to Disease / 9.9:
Renewal Processes / 10:
Renewal Processes when Time is Discrete / 10.1:
Renewal Processes when Time is Continuous / 10.3:
Alternating Renewal Processes / 10.4:
Markov Renewal Processes (Semi-Markov Processes) / 10.5:
Renewal Reward Processes / 10.6:
Statistical Inference for Renewal Processes / 10.7:
Stationary Processes and Time Series Analysis / 10.8:
Definition / 11.1:
Some Examples / 11.2:
Ergodic Theorems / 11.3:
Covariance Stationary Processes in the Frequency Domain / 11.4:
Time Series Analysis: Introduction / 11.5:
Stochastic Models for Time Series / 11.6:
The Autoregressive Process / 11.7:
The Moving Average Process / 11.8:
A Mixed Autoregressive Moving Average Process / 11.9:
Autoregressive Integrated Moving Average Processes / 11.10:
Time Series Analysis in the Time Domain / 11.11:
Spectral Analysis of Time Series Data / 11.12:
Simulation and Markov Chain Monte Carlo / 12:
Simulation / 12.1:
Markov Chain Monte Carlo / 12.3:
Answers to Selected Exercises
Appendix
Author Index
Subject Index
Preface
Stochastic Processes: Description and Definition / 1:
Introduction / 1.1:
7.

図書

図書
Alain Bensoussan, Jacques-Louis Lions ; English version edited, prepared, and produced by Trans-Inter-Scientia
出版情報: Amsterdam ; New York : North-Holland Pub. Co. , New York : Sole distributors for the U.S.A. and Canada, Elsevier North-Holland, 1982  xi, 564 p. ; 23 cm
シリーズ名: Studies in mathematics and its applications ; v. 12
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8.

図書

図書
editors, P.H. Damgaard and H. Hüffel
出版情報: Singapore : World Scientific, c1988  xii, 496 p. ; 26 cm
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9.

図書

図書
Yuri Kifer
出版情報: Boston ; Basel : Birkhäuser, 1988  294 p. ; 24 cm
シリーズ名: Progress in probability and statistics ; v. 16
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10.

図書

図書
Dimitri P. Bertsekas
出版情報: New York : Academic Press, 1976  xv, 397 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 125
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