Optimum and Adaptive Signal Processing
Optimal och adaptiv signalbehandling

BMEN15F, 7.5 högskolepoäng

Gäller från och med: Autumn 2018
Beslutad av: Professor Thomas Johansson
Datum för fastställande: 2018-10-08

Allmänna uppgifter

Avdelning: Biomedical Engineering
Kurstyp: Gemensam kurs, avancerad nivå och forskarnivå
Kursen ges även på avancerad nivå med kurskod: EITN60
Undervisningsspråk: English

Syfte

The course provides basic knowledge in statistical signal processing and the theory of optimal methods and how they can be applied. The course presents signal processing methodology and solutions to problems where digital systems tune in automatically and adapt to the environment. The student is given enough theoretical and practical knowledge to independently be able to formulate the mathematical problem, solve it and implement the solution for use with real-life signals.

Mål

Kunskap och förståelse

För godkänd kurs skall doktoranden

• have knowledge about and understand the main concepts in optimum and adaptive filter theory
• be able to apply the most commonly used methods to real problems and real-life signals (Matlab-level)
• be able to formulate mathematical problems based on described situations

Färdighet och förmåga

För godkänd kurs skall doktoranden

• be able to explain the main principles behind the most common adaptive methods (LMS and RLS)
• be able to explain/calculate the convergence and stability properties for these methods
• be able to sketch the most common block diagrams/structures used for adaptive filters and their properties
• be able to set parameters needed to make the algorithms work
• be able to foresee the consequences for the algorithms when implemented in fixed-point arithmetic
• be able to implement adaptive filters

Värderingsförmåga och förhållningssätt

För godkänd kurs skall doktoranden

• have the ability to analyze, evaluate and implement adaptive algorithms, and be able to interpret and describe the principles which they are based on.
• have the insight that many different technical problems can be solved using the same methods.

Kursinnehåll

Optimum filtering -Wiener filters -Linear prediciton -The Levinson-Durbin algorithm Basics about adaptive filters -From optimal to adaptive filters -Cost functions, minimization problems and iterative procedures -Convergence and tracking capability, implementation aspects -Strategies for how to connect adaptive filters The LMS family -Principle and derivation -Convergence analysis and parameter settings -Variants including Normalized LMS, Leaky LMS, Fast LMS and Sign LMS -Matlab implementation -LMS in fixed-point arithmetic -Principle and derivation -Parameter settings The RLS family -Aspects when used -Matlab implementation -Numerical properties

Kurslitteratur

Haykin, S.: Adaptive Filter Theory. Pearson Education, 2014. ISBN 9780273764083.

Kursens undervisningsformer

Undervisningsformer: Föreläsningar, laborationer, övningar, projekt. Exercises 14 h, computer exercises 14 h and laboratory work 2 x 4 h

Kursens examination

Examinationsformer: Skriftlig tentamen, skriftlig rapport
Betygsskala: Underkänd, godkänd
Examinator:

Antagningsuppgifter

Förutsatta förkunskaper: ESS040, EITF75 Digital Signal Processing or ETI265, EITA50 Signal Processing in Multimedia or EITF15 Signal processing - theory and applications.

Kurstillfällesinformation

Kontaktinformation och övrigt

Kursansvarig: Frida Sandberg <frida.sandberg@bme.lth.se>
Hemsida: http://bme.lth.se/course-pages/optimal-och-adaptiv-signalbehandling/optimum-and-adaptive-signal-processing/