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Identification of Dynamic Systems
Least Squares Parameter Estimation for Dynamic Processes
other
Author(s):
Rolf Isermann
,
Marco Münchhof
Publication date
(Online):
November 4 2010
Publisher:
Springer Berlin Heidelberg
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The Dynamic Brain
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Linear prediction: A tutorial review
Nadine Makhoul
(1975)
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Maximum entropy spectral analysis and autoregressive decomposition
Tad J. Ulrych
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Thomas Bishop
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System identification—A survey
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Author and book information
Book Chapter
Publication date (Print):
2011
Publication date (Online):
November 4 2010
Pages
: 223-290
DOI:
10.1007/978-3-540-78879-9_9
SO-VID:
cc8391cb-08df-4642-b43d-16f4af1f5c4d
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Book chapters
pp. 1
Introduction
pp. 33
Mathematical Models of Linear Dynamic Systems and Stochastic Signals
pp. 77
Spectral Analysis Methods for Periodic and Non-Periodic Signals
pp. 99
Frequency Response Measurement with Non-Periodic Signals
pp. 121
Frequency Response Measurement for Periodic Test Signals
pp. 149
Correlation Analysis with Continuous Time Models
pp. 179
Correlation Analysis with Discrete Time Models
pp. 203
Least Squares Parameter Estimation for Static Processes
pp. 223
Least Squares Parameter Estimation for Dynamic Processes
pp. 291
Modifications of the Least Squares Parameter Estimation
pp. 319
Bayes and Maximum Likelihood Methods
pp. 335
Parameter Estimation for Time-Variant Processes
pp. 353
Parameter Estimation in Closed-Loop
pp. 369
Parameter Estimation for Frequency Responses
pp. 379
Parameter Estimation for Differential Equations and Continuous Time Processes
pp. 409
Subspace Methods
pp. 429
Parameter Estimation for MIMO Systems
pp. 453
Parameter Estimation for Non-Linear Systems
pp. 469
Iterative Optimization
pp. 501
Neural Networks and Lookup Tables for Identification
pp. 539
State and Parameter Estimation by Kalman Filtering
pp. 555
Numerical Aspects
pp. 565
Practical Aspects of Parameter Estimation
pp. 605
Application Examples
pp. 685
Mathematical Aspects
pp. 691
Experimental Systems
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