{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":19,"n_cols":5,"rows_kept":19,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[3,2,3,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[11,2,11,3],[12,2,12,3],[16,2,16,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910438145803321"]
[null,null,"Titolo",null,"Model based parameter estimation : theory and applications / / Hans Georg Bock ... [et al.], editors"]
[null,null,"Pubbl/distr/stampa",null,"New York, : Springer, 2013"]
[null,null,"ISBN",null,"1-299-33664-7"]
[{"$nulls":4},"3-642-30367-6"]
[null,null,"Edizione",null,"[1st ed. 2013.]"]
[null,null,"Descrizione fisica",null,"1 online resource (339 p.)"]
[null,null,"Collana",null,"Contributions in mathematical and computational sciences ; ; v. 4"]
[null,null,"Disciplina",null,"515.3"]
[null,null,"Soggetti",null,"Stochastic systems"]
[{"$nulls":4},"Parameter estimation"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Parameter Estimation and Optimum Experimental Design for Differential Equation Models: H.G. Bock, St. Körkel, J.P. Schlöder -- Adaptive Finite Element Methods for Parameter Identification Problems: B. Vexler -- Gauss-Newton Methods for Robust Parameter Estimation: T. Binder, E. Kostina -- An Optimal Scanning Sensor Activation Policy for Parameter Estimation of Distributed Systems: D. Ucínski -- Interaction between Experiment, Modeling and Simulation of Spatial Aspects in the JAK2/STAT5 Signaling Pathway: E. Friedmann, A. C. Pfeifer, R. Neumann, U. Klingmüller , R. Rannacher -- The Importance and Challenges of Bayesian Parameter Learning in Systems Biology: J. Mazur, L. Kaderali -- Experiment Setups and Parameter Estimation in Fluorescence Recovery After Photobleaching Experiments: A Review of Current Practice: J. Beaudouin, M. S. Mommer, H. G. Bock, R. Eils -- Drug Resistance in Infectious Diseases: Modeling, Parameter Estimation and Numerical Simulation: Le Thi Thanh An, W. Jäger -- Mathematical Models of Hematopoietic Reconstitution after Stem Cell Transplantation: A. Marciniak-Czochra, Th. Stiehl -- Combustion Chemistry and Parameter Estimation: M. Fischer, U. Riedel -- Numerical Simulation of Catalytic Reactors by Molecular-Based Models: O. Deutschmann, St. Tischer -- Model-Based Design of Experiments for Estimating Heat-Transport Parameters in Tubular Reactors: A.Badinski, D. Corbett -- Parameter Estimation for a Reconstructed SOFC Mixed-Conducting LSCF-Cathode: Th. Carraro, J. Joos -- An Application of Robust Parameter Estimation in Environmental Physics: G. Herzog, F. R. Vogel -- Parameter Estimation in Image Processing and Computer "]
[{"$nulls":4},"Vision: Ch. S. Garbe, B. Ommer."]
[null,null,null,"Sommario/riassunto","This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental design in a range of contexts. These include fields as diverse as biology, medicine, chemistry, environmental physics, image processing and computer vision. The material chosen was presented at a multidisciplinary workshop on parameter estimation held in 2009 in Heidelberg. The contributions show how indispensable efficient methods of applied mathematics and computer-based modeling can be to enhancing the quality of interdisciplinary research.   The use of scientific computing to model, simulate, and optimize complex processes has become a standard methodology in many scientific fields, as well as in industry. Demonstrating that the use of state-of-the-art optimization techniques in a number of research areas has much potential for improvement, this book provides advanced numerical methods and the very latest results for the applications under consideration."]