PreprintCC BY-NC-ND 4.0HAL
Measure and integration
Abstract
This is an introduction to measure theory, integration and function spaces, with all the needed preliminaries included, and with some applications included as well. We first discuss some basic motivations, coming from discrete probability, that we develop in detail, as a preliminary to general measure theory. Then we discuss measure theory, integration and function spaces, all developed in a standard way, and with emphasis on the explicit computation of various integrals. Finally, we come back to probability, discrete and continuous, with a more advanced discussion, of quantum flavor.
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BibTeX
@misc{banica2026measure,
title = {{Measure and integration}},
author = {Teo Banica},
howpublished = {HAL},
year = {2026},
month = oct,
url = {https://hal.science/hal-05119475v2},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Measure and integration
AU - Teo Banica
PY - 2026
DA - 2026/10/05
PB - HAL
UR - https://hal.science/hal-05119475v2
AB - This is an introduction to measure theory, integration and function spaces, with all the needed preliminaries included, and with some applications included as well. We first discuss some basic motivations, coming from discrete probability, that we develop in detail, as a preliminary to general measure theory. Then we discuss measure theory, integration and function spaces, all developed in a standard way, and with emphasis on the explicit computation of various integrals. Finally, we come back to probability, discrete and continuous, with a more advanced discussion, of quantum flavor.
ER -