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AuthorWalter, Eric. author
TitleIdentifiability of State Space Models [electronic resource] : with applications to transformation systems / by Eric Walter
ImprintBerlin, Heidelberg : Springer Berlin Heidelberg, 1982
Connect tohttp://dx.doi.org/10.1007/978-3-642-61823-9
Descript 216 p. online resource

CONTENT

1. Transformation Systems -- 1.1 Introduction -- 1.2 Formalism -- 1.3 An example: nonlinear chemical kinetics -- 1.4 Specific problems of transformation system modelling -- 1.5 Conclusion -- 2. Structural Properties and Main Approaches to Checking Them -- 2.1 Introduction -- 2.2 Definitions -- 2.3 Practical methods for checking structural observability and structural controllability of linear models -- 2.4 Main approaches to structural identifiability -- 2.5 Conclusion -- 3. Local Identifiability -- 3.1 Introduction -- 3.2 Methods -- 3.3 Linear models -- 3.4 Computer aided design of models -- 3.5 Implementation for linear transformation systems -- 3.6 Conclusion -- 4. Global Identifiability of Linear Models -- 4.1 Introduction -- 4.2 Properties of the transition matrix -- 4.3 Parametrization of the transition matrix -- 4.4 Application to checking s.g. identifiability -- 4.5 Conclusion -- 5. Exhaustive Modelling for Linear Models -- 5.1 Introduction -- 5.2 Class of the studied models -- 5.3 The matrices B and C are known -- 5.4 The matrices B and C are partially unknown -- 5.5 Connections with Kalmanโ{128}{153}s canonical form -- 5.6 Applications of exhaustive modelling -- 5.7 Conclusion -- 6. Examples -- 6.1 Introduction -- 6.2 Chemotherapeutic model -- 6.3 Hepatobiliary kinetics of B.S.P. -- 6.4 Metabolism of iodine -- 6.5 Systemic distribution of Vincamine -- 6.6 Conclusion -- 7. Global Identifiability of Nonlinear Models -- 7.1 Introduction -- 7.2 Series expansion approach -- 7.3 Linearization approach -- 7.4 Conclusion -- Conclusion -- References


Mathematics Mathematical models Biomathematics Statistics Mathematics Mathematical and Computational Biology Mathematical Modeling and Industrial Mathematics Statistics for Life Sciences Medicine Health Sciences



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