Adobe PDF
(1.2 MB)
| Title Details: | |
|
Random Variables and Stochastic Processes |
|
| Authors: |
Stafylopatis, Andreas-Georgios Siolas, Georgios |
| Description: | |
| Abstract: |
After a brief reminder of the basic concepts of probability theory (random variables, probability distributions, summarization, mean, variance), stochastic processes are defined based on probabilities. The Poisson process, birth-death processes and Markov processes (continuous and discrete-time) are treated in particular. The basic properties and main theorems for solving Markovian models in the steady state are presented and examples of their use for the analysis of computer systems are given.
|
| Linguistic Editors: |
Pappas, Vasilios |
| Technical Editors: |
Siolas, Georgios |
| Type: |
Chapter |
| Creation Date: | 11-03-2025 |
| Item Details: | |
| License: |
Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| Handle | http://hdl.handle.net/11419/14588 |
| Bibliographic Reference: | Stafylopatis, A., & Siolas, G. (2025). Random Variables and Stochastic Processes [Chapter]. In Stafylopatis, A., & Siolas, G. 2025. Performance Analysis of Computer Systems [Undergraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/14588 |
| Language: |
Greek |
| Is Part of: |
Performance Analysis of Computer Systems |
| Version: |
2η έκδ. |
| Publication Origin: |
Kallipos, Open Academic Editions |