ELEC-C5310 - Introduction to estimation, detection and learning, Lecture, 12.1.2022-7.4.2022

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

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: 12.01.2022 - 07.04.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Sergiy Vorobyov, Visa Koivunen, Esa Ollila

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 approximately 50 h, independent work approximately 83 h, total 133 h

    Attendance in some contact teaching may be compulsory.

DETAILS

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    8 Decent Work and Economic Growth

    9 Industry, Innovation and Infrastructure

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 No teaching
    2023-2024 Autumn I - II

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof