Estimation Theory: Mathematical and Statistical Basics

What it is about

You will learn the mathematical and statistical foundations of modern estimation methods. The module conveys probabilistic fundamentals, methods for detection and classification, optimal parameter estimation, model selection, as well as procedures for dynamic state estimation and signal reconstruction. In the end you can solve basic estimation problems, evaluate suitable methods, and apply them in practical applications.

What you will be able to do

• Understand mathematical foundations of probability theory
• Analyze potentials and limits of various estimation methods
• Solve basic estimation problems
• Evaluate applicability of estimation models
• Perform model selection
• Perform signal reconstruction

What the module consists of

• VorlesungDelivery of theoretical content on estimation, model selection and special procedures
• Tutorium/ÜbungPractice and deepening of lecture content with practical examples; includes programming tasks

Teaching method

• Vorlesung in Präsenz mit Folien und TafelzeichnungenExplanation of theory and presentation of central results
• Praktische Beispiele und DiskussionenEncourage engagement with current content
• Tutorien und ProgrammieraufgabenPromote understanding through application to real data
• Elektronische Präsentationen und HandoutsSupport self-study and revision