Mathematical Statistics: Stationary and Non-stationary Spectral Analysis

This course offers advanced knowledge in spectral analysis, a powerful method for analysing both stationary and non-stationary signals. Learn how to interpret and apply various techniques for estimating spectra, both parametric and non-parametric, and how to handle signals that change over time or are sampled unevenly.

You will also be introduced to spatial spectral analysis and advanced techniques such as the Wigner-Ville distribution and multi-window analysis. The course is ideal if you want to understand how to analyse complex signals in fields like engineering, natural sciences, or economics.

The course is elective in some specialisations within the Bachelor’s or Master’s programmes in science at Lund University. It can also be taken a stand-alone course.

Teaching consists of lectures, lab sessions, and assignments. The labs are hands-on sessions where you apply the methods in practice, and they are mandatory. The assignments, both written and oral, allow you to demonstrate your understanding and ability to apply the theory.

Assessment is based on submitted assignments and lab reports.

Prerequisites

Knowledge corresponding to MASC04 Stationary Stochastic Processes, 7,5 ECTS, and MASM17 Time series analysis, 7,5 ECTS. English course 6/B (advanced proficiency).

Selection criteria

Seats are allocated according to: ECTS (HPAV): 100 %.

Tuition fees for non-EU/EEA citizens

Citizens of countries outside:

• The European Union (EU)
• The European Economic Area (EEA) and
• Switzerland

are required to pay tuition fees. You pay an instalment of the tuition fee in advance of each
semester.

Tuition fees, payments and exemptions

Full programme/course tuition fee: SEK 21,250
First payment: SEK 21,250

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Note that you may also need to pay an application fee, or provide proof of exemption.

Application fee

No tuition fees for citizens of the EU, EEA and Switzerland

There are no tuition fees for citizens of the European Union (EU), the European Economic Area (EEA) and Switzerland.