The Assay of Spatially Random Material: Mathematics and Its Applications, cartea 20
Autor Yakov Ben-Haimen Limba Engleză Paperback – 21 apr 2014
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Specificații
ISBN-13: 9789401088930
ISBN-10: 9401088934
Pagini: 340
Ilustrații: XVIII, 318 p.
Dimensiuni: 152 x 229 x 18 mm
Greutate: 0.45 kg
Ediția:1985
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Mathematics and Its Applications
Locul publicării:Dordrecht, Netherlands
ISBN-10: 9401088934
Pagini: 340
Ilustrații: XVIII, 318 p.
Dimensiuni: 152 x 229 x 18 mm
Greutate: 0.45 kg
Ediția:1985
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Mathematics and Its Applications
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
1 Introduction.- 1.1 The Nature of the Problem.- 1.2 Examples of Spatially Random Material.- 1.3 Notes.- 2 Deterministic Design I: Conceptual Formulation.- 2.1 Relative Mass Resolution.- 2.2 Response Functions.- 2.3 Point-Source Response Sets.- 2.4 The Convexity Theorem: Complete Response Sets.- 2.5 Relative Mass Resolution and the Concept of Expansion.- 2.6 Example: Pu Assay With One Detector.- 2.7 Example: Pu Assay With Two Detectors.- 2.8 Example: Coincidence Measurements.- 2.9 Computation of the Relative Mass Resolution.- 2.10 Example: Pu Assay With Four Detectors.- 2.11 The Inclusion of Statistical Uncertainty.- 2.12 Example: Radioactive Waste Assay.- 2.13 Summary.- 2.14 Notes.- 3 Deterministic Design II: General Formulation.- 3.1 Motivation.- 3.2 Unconstrained Spatial Distributions.- 3.3 Constrained Spatial Distributions.- 3.4 Example: Simple Constrained Distributions.- 3.5 Example: Constrained Normal Distributions.- 3.6 Example: Meteorological Measurements.- 3.7 Example: Assay of a Pulmonary Aerosol.- 3.8 Example: Thickness Measurement.- 3.9 Example: Enrichment Assay.- 3.10 Auxiliary Parameters.- 3.11 Example: Variable Matrix Structure.- 3.12 Variable Spatial Distributions and Auxiliary Parameters.- 3.13 Constrained Time-Varying Distributions.- 3.14 Example: Flow-Rate Measurement.- 3.15 Notes.- 4 Probabilistic Interpretation of Measurement.- 4.1 Probability Density of the Measurement.- 4.2 Probability Density of the Total Source Mass.- 4.3 Bayes’ Decision Theory.- 4.4 Neyman-Pearson Decision Theory.- 4.5 Direct Probabilistic Calibration.- 4.6 Summary.- 4.7 Notes.- 5 Probabilistic Design.- 5.1 Motivation.- 5.2 Relative Error Criterion.- 5.3 Minimum Variance Criterion.- 5.4 Probabilistic Expansion.- 5.5 Notes.- 6 Adaptive Assay.- 6.1 Motivation.- 6.2 SequentialAnalysis.- 6.3 Adaptive Barrel Assay.- 6.4 Adaptive Assay of a Pulmonary Aerosol.- 6.5 Adaptive Assay of a Uranium Deposit.- 6.6 Notes.- 7 Some Directions For Research.- 7.1 Overview.- 7.2 Nonlinearity in Mass.- 7.3 Non-Convex Response Sets.- 7.4 Asymptotic Designs.- 7.5 Malfunction Isolation.- 7.6 Adaptive Assay: Advanced Concepts.- 7.7 Notes.- Author Index.