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Data Reconciliation And Gross Error Detection Book

Data Reconciliation And Gross Error Detection
Data Reconciliation And Gross Error Detection, This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustiv, Data Reconciliation And Gross Error Detection has a rating of 3 stars
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Data Reconciliation And Gross Error Detection, This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustiv, Data Reconciliation And Gross Error Detection
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  • Data Reconciliation And Gross Error Detection
  • Written by author Dr. Shankar Narasimhan, Ph.D. Ch.E
  • Published by Elsevier Science, November 1999
  • This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustiv
  • This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustiv
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: Introduction. Measurement Errors and Error Reduction Techniques. Steady State Data Reconciliation for Bilinear Systems. Nonlinear Steady State Data Reconciliation. Data Reconciliation in Dynamic Systems. Introduction to Gross Error Detection. Multiple Gross Error Identification Strategies for Steady State Processes. Gross Error Detection in Dynamic Processes. Design of Sensor Networks. Industrial Applications of Data Reconciliation and Gross Error Detection Technologies. Appendix A: Basic concepts of linear algebra. Appendix B: Basic concepts of Graph Theory. Appendix C: Statistical Hypotheses Testing.


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Data Reconciliation And Gross Error Detection, This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustiv, Data Reconciliation And Gross Error Detection

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Data Reconciliation And Gross Error Detection, This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustiv, Data Reconciliation And Gross Error Detection

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Data Reconciliation And Gross Error Detection, This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustiv, Data Reconciliation And Gross Error Detection

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