Subject Area | Signals, Communications, and Networking |
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Semester | Semester 8 – Spring |
Type | Elective |
Teaching Hours | 4 |
ECTS | 6 |
Course Site | http://eclass.uth.gr |
Course Director |
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Course Instructor |
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Scientific Responsible |
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Title | MLSysOps: Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum |
Duration | 2023 – 2025 |
Site | https://csl.e-ce.uth.gr/projects/mlsysops |
Scientific Responsible |
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Title | VEPIT: Vessel Energy Profiling based on IoT |
Duration | 2022 – 2024 |
Site | https://csl.e-ce.uth.gr/projects/vepit |
Department of Electrical and Computer Engineering | |
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Tel. | +30 24210 74967 |
gece ΑΤ e-ce.uth.gr | |
PGS Tel. | +30 24210 74934 |
PGS e-mail | pgsec ΑΤ e-ce.uth.gr |
URL | https://www.e-ce.uth.gr/contact-info/?lang=en |
Subject Area | Signals, Communications, and Networking |
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Semester | Semester 8 – Spring |
Type | Elective |
Teaching Hours | 4 |
ECTS | 6 |
Course Site | http://eclass.uth.gr |
Course Director |
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Course Instructor |
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The course focuses on the understanding of advanced mathematical tools from probability and statistics and their application in telecommunication systems and signal processing. In the first part of the course the student is introduces to the mathematical tools for many random variables, vectors ad the understanding of the concept of the data model. Next especial emphasis is given to the understanding of estimation and detection techniques. The third objective of the curse is to introduce the students to the necessary techniques for modeling physical phenomena with random processes. The learning outcomes of the course are achieved after executing a large number of homeworks and (6-7) and MATLAB pojects.
After successfully completing the course the student will be in a position to: