Course syllabus

# Optimal signalbehandling Optimum Signal Processing

## ETTN10, 7,5 credits, A (Second Cycle)

Valid for: 2013/14
Decided by: Education Board A
Date of Decision: 2013-04-15

## General Information

Elective for: C4, C4-ssr, D4, D4-ssr, E4, E4-mt, E4-bg, E4-ssr, F5, F5-ssr, MWIR2, Pi4, Pi4-ssr
Language of instruction: The course will be given in English on demand

## Aim

The course gives the basic knowledge in statistical signal processing and treats the theory and applications of optimal methods in filter design. The filter design methods are based on the statistical properties of the information signals as well as the additive noise.

## Learning outcomes

Knowledge and understanding
For a passing grade the student must

• be able to apply optimal methods in signal modelling
• be able to apply optimal methods in processing signals in noisy environments

Competences and skills
For a passing grade the student must

• have knowledge of problem formulations applied to signal modelling
• have knowledge of using statistical methods in estimation of signals in noise

Judgement and approach
For a passing grade the student must

• be able to read literature as well as treat with standards in this area

## Contents

The following items are treated in the course: Matrices, random processes, spectral factorization. Signal modelling (IIR/FIR) using the Prony’ method. Normal equation and Levinson-Durbin recursive method, lattice filters. Estimation of reflection coefficients using Burgs algorithm. Optimal IIR and FIR filters (‘Wiener filters’), linear prediction, noise cancellation. Spectral estimation using non-parametric methods. Eigenvector methods in estimation of sinusoids in noise (Pisarenko, Music).

Applications: Filter for optimal noise cancellations are used in a wide area, i.e. mobile communication, acoustical signal processing, biomedical signals (EEG, ECG ). Spectral estimation has also a wide area of applications. Fast algorithms in signal processing are of great importance for VLSI design.

## Examination details

Assessment: Written exam, fulfilled laboratory work and partial tests during the course.

Parts
Code: 0112. Name: Optimum Signal Processing.
Credits: 6. Grading scale: TH. Assessment: Written examination.
Code: 0212. Name: Project in Signal Processing.
Credits: 1,5. Grading scale: UG. Assessment: Project report.

Required prior knowledge: ESS040 Digital Signal Processing or ETI265 Signal Processing in Multimedia or EITF15 Signal Processing - Theory and Applications.
The number of participants is limited to: No
The course overlaps following course/s: ETT074