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Title Handbook of dynamic data driven applications systems / Erik Blasch, Sai Ravela, Alex Aved, editors
Published Cham, Switzerland : Springer, [2018]
Online access available from:
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Description 1 online resource
Contents Intro; Contents; About the Editors; 1 Introduction to Dynamic Data Driven Applications Systems; 1.1 Introduction; 1.2 What Is DDDAS?; 1.3 State Estimation and Data Assimilation; 1.3.1 DDDAS and Adaptive State Estimation; 1.3.2 Does DDDAS Use Feedback Control?; 1.4 DDDAS Methods; 1.5 DDDAS Research Areas of Historical Development; 1.5.1 Theory: Modeling and Analysis; 1.5.2 Methods: Domain Applications; 1.5.3 Design: Systems and Architectures; 1.6 Book Overview; 1.7 DDDAS Future; 1.8 Summary; References; Part I Measurement-Aware: Data Assimilation, Uncertainty Quantification
2 Tractable Non-Gaussian Representations in Dynamic Data Driven Coherent Fluid Mapping2.1 Introduction; 2.1.1 Systems Dynamics and Optimization; 2.1.2 Dynamically Deformable Reduced Models; 2.1.3 Nonlinear High Dimensional Inference; 2.2 Ensemble Learning in Mixture Ensembles; 2.2.1 Mixture Ensemble Filter and Smoother; 2.3 Nonlinear Filtering Must Reduce Total Variance; 2.4 Ensemble Learning with a Stacked Cascade; 2.4.1 Application Example; 2.5 Information Theoretic Learning in Filtering; 2.5.1 Tractable Information Theoretic Approach; 2.6 Application Example; 2.7 Conclusions; References
3 Dynamic Data-Driven Adaptive Observations in Data Assimilation for Multi-scale Systems3.1 Introduction; 3.2 Dimensional Reduction and Homogenization; 3.3 Data Assimilation in Multi-scale Systems; 3.4 Information-Theoretic Sensor Selection Strategy; 3.4.1 The Linear Case; 3.4.2 Information Flow for the Coarse Grained Dynamics; 3.4.3 Finite-Time Lyapunov Exponents and Singular Vectors; 3.4.4 Sensor Selection and the Lorenz 1963 Model; Sensor Selection with Kullback-Leibler Divergence; Sensor Selection with Singular Vectors Influence of Singular Values in Discrete-Time, Linear Gaussian Case3.4.4.4 Numerical Results; 3.5 Conclusions; References; 4 Dynamic Data-Driven Uncertainty Quantification via Polynomial Chaos for Space Situational Awareness; 4.1 Introduction; 4.2 Gaussian Mixture Models; 4.3 Polynomial Chaos; 4.4 Polynomial Chaos with Gaussian Mixture Models; 4.5 Global Ionosphere-Thermosphere Model; 4.6 Results; 4.6.1 Orbital Uncertainty Quantification; 4.6.2 Initial Results for Atmospheric Density Forecasting; 4.7 Conclusion; References; Part II Signals-Aware: Process Monitoring
5 Towards Learning Spatio-Temporal Data Stream Relationships for Failure Detection in Avionics5.1 Introduction; 5.2 Background; 5.2.1 Error Detection and Correction Methods; 5.2.2 Spatio-Temporal Data Stream Processing System; 5.3 Design of Machine Learning Component; 5.3.1 Prediction in PILOTS Programming Language; 5.3.2 Prediction in PILOTS Runtime; 5.4 Data-Driven Learning of Linear Models; 5.4.1 Learning Algorithm; 5.4.2 Linear Model Accuracy; 5.5 Statistical Learning of Dynamic Models; 5.5.1 Offline Supervised Learning; Gaussian Naïve Bayes Classifiers
Summary The Handbook of Dynamic Driven Applications Systems establishes an authoritative reference of DDDAS, pioneered by Dr. Darema and the co-authors for researchers and practitioners developing DDDAS technologies. Beginning with general concepts and history of the paradigm, the text provides 32 chapters by leading experts in10 application areas to enable an accurate understanding, analysis, and control of complex systems; be they natural, engineered, or societal: Earth and Space Data Assimilation Aircraft Systems Processing Structures Health Monitoring Biological Data Assessment Object and Activity Tracking Embedded Control and Coordination Energy-Aware Optimization Image and Video Computing Security and Policy Coding Systems Design The authors explain how DDDAS unifies the computational and instrumentation aspects of an application system, extends the notion of Smart Computing to span from the high-end to the real-time data acquisition and control, and manages Big Data exploitation with high-dimensional model coordination
Bibliography Includes bibliographical references and index
Notes Online resource; title from PDF title page (EBSCO, viewed November 16, 2018)
Subject Computer simulation.
System design.
Form Electronic book
Author Aved, Alex, editor
Blasch, Erik, editor
Ravela, Sai, editor
ISBN 3319955047 (electronic bk.)
9783319955049 (electronic bk.)