Data Reconciliation and Gross Error Detection. An Intelligent Use of Process Data [#432634]

Data Reconciliation and Gross Error Detection. An Intelligent Use of Process Data By Shankar Narasimhan and Cornelius Jordache (Auth.)
2000 | 411 Pages | ISBN: 0884152553 | PDF | 6 MB
This is an excellent book on the subject - the authors have covered all the bases. If you want a book on data reconciliation and gross error detection, this is as complete and thorough a book as I can imagine. - Les A. Kane, Editor, Advanced Process Control and Information Systems Content: Acknowledgments, Pages xiii-xivPreface, Pages xv-xvii1 - The Importance of Data Reconciliation and Gross Error Detection, Pages 1-312 - Measurement Errors and Error Reduction Techniques, Pages 32-583 - Linear Steady-State Data Reconciliation, Pages 59-844 - Steady-State Data Reconciliation for Bilinear Systems, Pages 85-1185 - Nonlinear Steady-State Data Reconciliation, Pages 119-1416 - Data Reconciliation in Dynamic Systems, Pages 142-1737 - Introduction to Gross Error Detection, Pages 174-2258 - Multiple Gross Error Identification Strategies for Steady-State Processes, Pages 226-2809 - Gross Error Detection in Linear Dynamic Systems, Pages 281-29910 - Design of Sensor Networks, Pages 300-32611 - Industrial Applications of Data Reconciliation and Gross Error Detection Technologies, Pages 327-372Appendix A - Basic Concepts in Linear Algebra, Pages 373-377Appendix B - Graph Theory Fundamentals, Pages 378-383Appendix C - Fundamentals of Probability and Statistics, Pages 384-393Index, Pages 394-402Author Index, Pages 403-405The Authors, Page 406