LEARNING OUTCOMES
Develop understanding and skills for using the tools of probability, signal and systems and learning theory to estimate signals and parameters of interest, to detect events from data, and to learn from data. Develop understanding of multivariate analysis as well. Develop understanding how to identify the optimal estimator/detector or at least bound the performance of any estimator/detector. Develop understanding and skills for using detection approaches (statistical hypotheses testing). Understanding radar detection. Practicing basic concepts such as: sufficient statistics, bias and mean squared error, maximum likelihood, Bayesian estimation and learning.
Credits: 5
Schedule: 10.09.2024 - 26.11.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Sergiy Vorobyov, Esa Ollila, Visa Koivunen
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Statistical modeling and basic distributions. Parameter estimation. Hypothesis testing detection theory. Basics of learning theory.
Assessment Methods and Criteria
valid for whole curriculum period:
Lectures, exercises, assignments, final exam.
Workload
valid for whole curriculum period:
Lectures, exercises, assignments, final exam, independent.
Attendance in some contact teaching may be compulsory.
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn I - II
2025-2026 Autumn I - II