close
1.

図書

図書
Giovanni Petris, Sonia Petrone, Patrizia Campagnoli
出版情報: New York : Springer, c2009  xiii, 251 p. ; 24 cm
シリーズ名: Use R! / series editors, Robert Gentleman, Kurt Hornik, Giovanni Parmigiani
所蔵情報: loading…
目次情報: 続きを見る
Introduction: basic notions about Bayesian inference / 1:
Basic notions / 1.1:
Simple dependence structures / 1.2:
Synthesis of conditional distributions / 1.3:
Choice of the prior distribution / 1.4:
Bayesian inference in the linear regression model / 1.5:
Markov chain Monte Carlo methods / 1.6:
Gibbs sampler / 1.6.1:
Metropolis-Hastings algorithm / 1.6.2:
Adaptive rejection Metropolis sampling / 1.6.3:
Problems
Dynamic linear models / 2:
Introduction / 2.1:
A simple example / 2.2:
State space models / 2.3:
Dynamic linear models in package dlm / 2.4:
Examples of nonlinear and non-Gaussian state space models / 2.6:
State estimation and forecasting / 2.7:
Filtering / 2.7.1:
Kalman filter for dynamic linear models / 2.7.2:
Filtering with missing observations / 2.7.3:
Smoothing / 2.7.4:
Forecasting / 2.8:
The innovation process and model checking / 2.9:
Controllability and observability of time-invariant DLMs / 2.10:
Filter stability / 2.11:
Model specification / 3:
Classical tools for time series analysis / 3.1:
Empirical methods / 3.1.1:
ARIMA models / 3.1.2:
Univariate DLMs for time series analysis / 3.2:
Trend models / 3.2.1:
Seasonal factor models / 3.2.2:
Fourier form seasonal models / 3.2.3:
General periodic components / 3.2.4:
DLM representation of ARIMA models / 3.2.5:
Example: estimating the output gap / 3.2.6:
Regression models / 3.2.7:
Models for multivariate time series / 3.3:
DLMs for longitudinal data / 3.3.1:
Seemingly unrelated time series equations / 3.3.2:
Seemingly unrelated regression models / 3.3.3:
Hierarchical DLMs / 3.3.4:
Dynamic regression / 3.3.5:
Common factors / 3.3.6:
Multivariate ARMA models / 3.3.7:
Models with unknown parameters / 4:
Maximum likelihood estimation / 4.1:
Bayesian inference / 4.2:
Conjugate Bayesian inference / 4.3:
Unknown covariance matrices: conjugate inference / 4.3.1:
Specification of Wt by discount factors / 4.3.2:
A discount factor model for time-varying Vt / 4.3.3:
Simulation-based Bayesian inference / 4.4:
Drawing the states given y1:T: forward filtering backward sampling / 4.4.1:
General strategies for MCMC / 4.4.2:
Illustration: Gibbs sampling for a local level model / 4.4.3:
Unknown variances / 4.5:
Constant unknown variances: d Inverse Gamma Prior / 4.5.1:
Multivariate extensions / 4.5.2:
A model for outliers and structural breaks / 4.5.3:
Further examples / 4.6:
Estimating the output gap: Bayesian inference / 4.6.1:
Factor models / 4.6.2:
Sequential Monte Carlo methods / 5:
The basic particle filter / 5.1:
Auxiliary particle filter / 5.1.1:
Sequential Monte Carlo with unknown parameters / 5.3:
A simple example with unknown parameters / 5.3.1:
Concluding remarks / 5.4:
Useful distributions / A:
Matrix algebra: Singular Value Decomposition / B:
Index
References
Introduction: basic notions about Bayesian inference / 1:
Basic notions / 1.1:
Simple dependence structures / 1.2:
2.

図書

図書
H.H. Rosenbrock
出版情報: London : Nelson, 1970  viii, 257 p. ; 24 cm
シリーズ名: Studies in dynamical systems
所蔵情報: loading…
3.

図書

図書
Bernard Friedland
出版情報: New York ; Tokyo : McGraw-Hill, c1986  xiv, 513 p. ; 25 cm
シリーズ名: McGraw-Hill series in electrical engineering ; . Control theory
所蔵情報: loading…
目次情報: 続きを見る
Preface
Feedback Control / Chapter 1:
The Mechanism of Feedback / 1.1:
Feedback Control Engineering / 1.2:
Control Theory Background / 1.3:
Scope and Organization of This Book / 1.4:
Notes
References
State-Space Representation of Dynamic Systems / Chapter 2:
Mathematical Models / 2.1:
Physical Notion of System State / 2.2:
Block-Diagram Representations / 2.3:
Lagrange's Equations / 2.4:
Rigid Body Dynamics / 2.5:
Aerodynamics / 2.6:
Chemical and Energy Processes / 2.7:
Problems
Dynamics of Linear Systems / Chapter 3:
Differential Equations Revisited / 3.1:
Solution of Linear Differential Equations in State-Space Form / 3.2:
Interpretation and Properties of the State-Transition Matrix / 3.3:
Solution by the Laplace Transform: The Resolvent / 3.4:
Input-Output Relations: Transfer Functions / 3.5:
Transformation of State Variables / 3.6:
State-Space Representation of Transfer Functions: Canonical Forms / 3.7:
Frequency-Domain Analysis / Chapter 4:
Status of Frequency-Domain Methods / 4.1:
Frequency-Domain Characterization of Dynamic Behavior / 4.2:
Block-Diagram Algebra / 4.3:
Stability / 4.4:
Routh-Hurwitz Stability Algorithms / 4.5:
Graphical Methods / 4.6:
Steady State Responses: System Type / 4.7:
Dynamic Response: Bandwidth / 4.8:
Robustness and Stability (Gain and Phase) Margins / 4.9:
Multivariable Systems: Nyquist Diagram and Singular Values / 4.10:
Controllability and Observability / Chapter 5:
Introduction / 5.1:
Where Do Uncontrollable or Unobservable Systems Arise? / 5.2:
Definitions and Conditions for Controllability and Observability / 5.3:
Algebraic Conditions for Controllability and Observability / 5.4:
Disturbances and Tracking Systems: Exogenous Variables / 5.5:
Shaping the Dynamic Response / Chapter 6:
Design of Regulators for Single-Input, Single-Output Systems / 6.1:
Multiple-Input Systems / 6.3:
Where Should the Closed-Loop Poles Be Placed? / 6.4:
Linear Observers / Chapter 7:
The Need for Observers / 7.1:
Structure and Properties of Observers / 7.2:
Pole-Placement for Single-Output Systems / 7.3:
Reduced-Order Observers / 7.4:
Compensator Design by the Separation Principle / Chapter 8:
The Separation Principle / 8.1:
Compensators Designed Using Full-Order Observers / 8.2:
Robustness: Effects of Modeling Errors / 8.3:
Selecting Observer Dynamics: Robust Observers / 8.5:
Summary of Design Process / 8.7:
Linear, Quadratic Optimum Control / Chapter 9:
Why Optimum Control? / 9.1:
Formulation of the Optimum Control Problem / 9.2:
Quadratic Integrals and Matrix Differential Equations / 9.3:
The Optimum Gain Matrix / 9.4:
The Steady State Solution / 9.5:
Disturbances and Reference Inputs: Exogenous Variables / 9.6:
General Performance Integral / 9.7:
Weighting of Performance at Terminal Time / 9.8:
Random Processes / Chapter 10:
Conceptual Models for Random Processes / 10.1:
Statistical Characteristics of Random Processes / 10.3:
Power Spectral Density Function / 10.4:
White Noise and Linear System Response / 10.5:
Spectral Factorization / 10.6:
Systems with State-Space Representation / 10.7:
The Wiener Process and Other Integrals of Stationary Processes / 10.8:
Kalman Filters: Optimum Observers / Chapter 11:
Background / 11.1:
The Kalman Filter is an Observer / 11.2:
Kalman Filter Gain and Variance Equations / 11.3:
Steady State Kalman Filter / 11.4:
The "Innovations" Process / 11.5:
Reduced-Order Filters and Correlated Noise / 11.6:
Stochastic Control: The Separation Theorem / 11.7:
Choosing Noise for Robust Control / 11.8:
Matrix Algebra and Analysis / Appendix:
Bibliography
Index of Applications
Index
Preface
Feedback Control / Chapter 1:
The Mechanism of Feedback / 1.1:
4.

図書

図書
Lotfi A. Zadeh & Charles A. Desoer
出版情報: Huntington, N.Y. : R. E. Krieger Pub. Co., 1979  xxi, 627 p. ; 24 cm
所蔵情報: loading…
5.

図書

図書
by Katsuhiko Ogata
出版情報: Englewood Cliffs, N.J. : Prentice-Hall, c1967  xi, 596 p. ; 24 cm
シリーズ名: Prentice-Hall electrical engineering series
Instrumentation and controls series
所蔵情報: loading…
6.

図書

図書
LaMar K. Timothy, Blair E.Bona
出版情報: New York : McGraw-Hill, c1968  ix, 406 p ; 23 cm
シリーズ名: McGraw-Hill series in electronic systems
所蔵情報: loading…
7.

図書

図書
Vladimír Strejc
出版情報: Chichester [Eng.] ; New York : Wiley, c1981  426 p. ; 25 cm
所蔵情報: loading…
8.

図書

図書
[by] Louis Padulo [and] Michael A. Arbib
出版情報: Philadelphia, Pa. : W.B. Saunders, 1974  xvii, 779 p ; 25 cm
所蔵情報: loading…
9.

図書

図書
David F. Delchamps
出版情報: New York ; Tokyo : Springer-Verlag, c1988  x, 425 p. ; 24 cm
所蔵情報: loading…
10.

図書

図書
Masanao Aoki
出版情報: Berlin ; Tokyo : Springer-Verlag, c1987  xi, 314 p. ; 25 cm
所蔵情報: loading…
文献の複写および貸借の依頼を行う
 文献複写・貸借依頼