Pavel Kovanic

Mathematical Gnostics (eBook, PDF)

Advanced Data Analysis for Research and Engineering Practice

• Format: PDF

Produktbeschreibung

The focus of the book will be concentrated to the step-by-step explanation of applications of the algorithms to real data which are met in daily practice by all data analysts, with particulr focus on chemcial engineering. The book will lead readers through all relevant tasks on one-dimensional, two-dimensional, and multi-dimensional data analysis.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 342
• Erscheinungstermin: 8. Februar 2023
• Englisch
• ISBN-13: 9780429805295
• Artikelnr.: 67249421

Autorenporträt

Pavel Kovanic (Born 1928) 1950-1955: Studied high voltage technology on the Technical University in Sverdlovsk (recently Ekaterinburg, Russia). 1956-1970: Researcher, head of a scientific department at the Nuclear Research Institute of the Czechoslovak Academy of Sciences. 1970-1995: Scientist at the Institute of the Automation and Theory of Information of the Czech Academy of Sciences. 1995-2018: As a retired scientist participated as a scientific consultant on several research projects including grants of European Union.

Inhaltsangabe

1. Introductory Kindergarten. 2. Axioms. 3. Introduction to Non-Standard
Thought. 4. Quantification. 5. Estimation and Ideal Gnostic Cycle. 6.
Geometry. 7. Aggregation. 8. Thermodynamics of Uncertain Data. 9. Kernel
estimation. 10. Probability Distribution Functions. 11. Applications of
Local Distributions. 12. On the Notion of Normality. 13. Applications of
Global Distribution Functions. 14. Data Censoring. 15. Gnostic
Thermodynamic Analysis of Data Uncertainty. 16. Robust Estimation of a
Constant. 17. Measuring the Data Uncertainty. 18. Homo- or Heteroscedastic
Data. 19. Gnostic Multidimensional Regression Models. 20. Data Filtering.
21. Decision Making in Mathematical Gnostics. 22. Comparisons. 23. Advanced
Production Quality Control. 24. Robust Correlation. 25. General Relations.

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1. Introductory Kindergarten. 2. Axioms. 3. Introduction to Non-Standard Thought. 4. Quantification. 5. Estimation and Ideal Gnostic Cycle. 6. Geometry. 7. Aggregation. 8. Thermodynamics of Uncertain Data. 9. Kernel estimation. 10. Probability Distribution Functions. 11. Applications of Local Distributions. 12. On the Notion of Normality. 13. Applications of Global Distribution Functions. 14. Data Censoring. 15. Gnostic Thermodynamic Analysis of Data Uncertainty. 16. Robust Estimation of a Constant. 17. Measuring the Data Uncertainty. 18. Homo- or Heteroscedastic Data. 19. Gnostic Multidimensional Regression Models. 20. Data Filtering. 21. Decision Making in Mathematical Gnostics. 22. Comparisons. 23. Advanced Production Quality Control. 24. Robust Correlation. 25. General Relations.