This undergraduate textbook offers a self-contained and concise introduction to measure theory and integration.
The author takes an approach to integration based on the notion of distribution. This approach relies on deeper properties of the Riemann integral which may not be covered in standard undergraduate courses. It has certain advantages, notably simplifying the extension to "fuzzy" measures, which is one of the many topics covered in the book.
This book will be accessible to undergraduate students who have completed a first course in the foundations of analysis. Containing numerous examples as well as fully solved exercises, it is exceptionally well suited for self-study or as a supplement to lecture courses.
This undergraduate textbook offers a self-contained and concise introduction to measure theory and integration.
The author takes an approach to integration based on the notion of distribution. This approach relies on deeper properties of the Riemann integral which may not be covered in standard undergraduate courses. It has certain advantages, notably simplifying the extension to "fuzzy" measures, which is one of the many topics covered in the book.
This book will be accessible to undergraduate students who have completed a first course in the foundations of analysis. Containing numerous examples as well as fully solved exercises, it is exceptionally well suited for self-study or as a supplement to lecture courses.
Provides a self-contained introduction to abstract measure theory and integration Includes full solutions to the exercises Discusses fuzzy measures and unconditional sums
Satish Shirali
Measure and integration Lebesgue measure Fubini and Tonelli theorems Fundamental theorem of calculus Cantor set Lebesgue differentiability theorem Absolute continuity Vitali covering theorem Fuzzy measure Product measure Outer measure