É. Walter – författare

In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.

In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.

In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.

Identifiability of Parametric Models provides a comprehensive presentation of identifiability. This book is divided into 11 chapters. Chapter 1 reviews the basic methods for structural identifiability testing. The methods that deal with large-scale models and propose conjectures on global identifiability are considered in Chapter 2, while the problems of initial model selection and generating the set of models that have the exact same input-output behavior are evaluated in Chapter 3. Chapters 4 and 5 cover nonlinear models. The relations between identifiability and the well-posedness of the estimation problem are analyzed in Chapter 6, followed by a description of the algebraic manipulations required for testing a model for structural controllability, observability, identifiability, or distinguishability in chapter 7. The rest of the chapters are devoted to the relations between identifiability and parameter uncertainty. This publication is beneficial to students and researchers aiming to acquire knowledge of the identifiability of parametric models.

It is the objective of Science to formalize the relationships between observed quantities. The motivations of such a modelling procedure are varied, but can rougnly be collected around two pOles. If one is concerned with process control, one wants to find a model which wl11 De aDle to predlct tne process Denavlor, taKlng lnto account tne applled lnputs. The model will then be evaluated on it5 ability to mimic the ob5e~ved input-output behavior under c:onditione; ae; vari"d ae; po

The symposium held at Freiburg on September 10th, 1983 had been con- cerned with methodical problems in early detection. chiefly of can- cer. The first lectures dealt with mathematical models. They were followed by contributions to the possibilities of obtaining the pa- rameters required by the models and for the assessment of the me- thods. The two final lectures outlined a monitoring system for rare diseases and some problems in early detecting heart and circulation diseases. The meeting had been organized by the Deutsche Gesellschaft fUr Me- dizinische Dokumentation. Informatik und Statistik (GMDS). Thus the programme committee was set up by the heads of the GMDS Arbeitsgrup- pen affected by the respective topics. namely Dr. Keil (epidemiology}. Prof *. Dr. NeiS (statistical methods). PD Dr. Schwartz (systematic preventive checkup and early detection). PD Dr. Trampisch (methods of prognosis and decision making) and the signer. This is a welcome opportunity to put on record my thanks to various people and organizations. The lecturers had elaborated their manus- cripts and some have revised them. The individual discussions had been conducted by Prof. Dr. Dietz. Prof. Dr.Michaelis. Prof. Dr.