Optimal Signal Processing ET2410 (ETD008)
The course is given for: ETS programme
Credit units: 7,5 ECTS
Level: D, 60-80 credit units
Subject: Electrical Engineering (Elektroteknik)
Study period: period 4.
Responsible teacher(s): Mikael Swartling, e-mail: email@example.com
Exam: Project-like one week home exam containing theory as well as programming assignments.
The goal of this course is to give background and knowledge in the theory of optimal and statistical signal processing. The course also gives insight and experience in applied signal processing problems. After the course, the student should be able to use and implement algorithms. The course covers three areas: Iterative methods to solve normal equations, signal modelling and spectrum estimation. Common throughout the course is finding solutions by solving Least Squares problems. The courses Functions- and Matrix Theory, Stochastic Processes and Adaptive Signal Processing, or similar, are prerequisites.
- Monson H. Hayes
Statistical Digital Signal Processing and Modeling
- Material from the department
The course is organized on It's Learning course management pages, where information and materials will be published during the course.
- Part I, Least Squares Estimation
Hayes, chapter 4.6
- Part II & III, Levinson Recursions
Hayes, chapter 5.2 (not 5.2.6 and 5.2.9), 5.3
- Part IV, Schur's Recursion, Lattice Filter
Hayes, chapter 6
- Part V, Padé Approximation, Prony's Method, Shanks' Method
Hayes, chapter 4.1, 4.2, 4.3, 4.4
- Part VI, Non-parametrical Spectrum Estimation
Hayes, chapter 8.2
- Part VII, Parametrical Spectrum Estimation
Hayes, chapter 8.3, 8.4, 8.5, 8.6, 8.7
For access to the course web page, contact Mikael Swartling (firstname.lastname@example.org).