Advanced Numerical Modeling and Signal Processing

What it is about

In this module you will learn and apply advanced methods of signal processing and numerical modeling. This includes wavelet and multiscale analysis, principal component analysis, methods of regression and finite elements, and the application to real datasets within the framework of an overarching project.

What you will be able to do

• Understand and apply advanced principles and methods of signal processing
• Understand and assess advanced methods of numerical modeling and regression theory
• Analyze data and time series, extract characteristic features, and evaluate results
• Apply methods to practical problems and analyses with real data

What the module consists of

• LectureConveys the theoretical foundations: Wavelets/MRA, regression theory, SVD, PCA, finite elements and project
• Laboratories/ExercisesWork on selected practical tasks related to lecture topics, implementation in Matlab, project work with real data

Teaching method

• Lecture (presentation and board work)Introduction and explanation of the theoretical content
• Labs and exercises (group work, practical tasks)Deepening and application of theory based on practical examples and data analyses
• Matlab as a working toolImplementation and evaluation of the exercises and laboratory tasks