227-0101-AAL Discrete-Time and Statistical Signal Processing
| Semester | Herbstsemester 2017 |
| Dozierende | H.‑A. Loeliger |
| Periodizität | jedes Semester wiederkehrende Veranstaltung |
| Lehrsprache | Englisch |
| Kommentar | Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit. |
Lehrveranstaltungen
| Nummer | Titel | Umfang | Dozierende | |
|---|---|---|---|---|
| 227-0101-AA R | Discrete-Time and Statistical Signal Processing Self-study course. No presence required. The underlying lecture is offered in autumn semester (Tuesday 13-17h). | 112s Std. | H.‑A. Loeliger |
Katalogdaten
| Kurzbeschreibung | The course introduces some fundamental topics of digital signal processing with a bias towards applications in communications: discrete-time linear filters, equalization, DFT, discrete-time stochastic processes, elements of detection theory and estimation theory, LMMSE estimation and LMMSE filtering, LMS algorithm, Viterbi algorithm. |
| Lernziel | The course introduces some fundamental topics of digital signal processing with a bias towards applications in communications. The two main themes are linearity and probability. In the first part of the course, we deepen our understanding of discrete-time linear filters. In the second part of the course, we review the basics of probability theory and discrete-time stochastic processes. We then discuss some basic concepts of detection theory and estimation theory, as well as some practical methods including LMMSE estimation and LMMSE filtering, the LMS algorithm, and the Viterbi algorithm. A recurrent theme throughout the course is the stable and robust "inversion" of a linear filter. |
| Inhalt | 1. Discrete-time linear systems and filters: state-space realizations, z-transform and spectrum, decimation and interpolation, digital filter design, stable realizations and robust inversion. 2. The discrete Fourier transform and its use for digital filtering. 3. The statistical perspective: probability, random variables, discrete-time stochastic processes; detection and estimation: MAP, ML, Bayesian MMSE, LMMSE; Wiener filter, LMS adaptive filter, Viterbi algorithm. |
| Skript | Lecture Notes. |
Leistungskontrolle
| Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) | |
Leistungskontrolle als Semesterkurs | |
| ECTS Kreditpunkte | 6 KP |
| Prüfende | H.-A. Loeliger |
| Form | Sessionsprüfung |
| Prüfungssprache | Englisch |
| Repetition | Die Leistungskontrolle wird in jeder Session angeboten. Die Repetition ist ohne erneute Belegung der Lerneinheit möglich. |
| Prüfungsmodus | schriftlich 180 Minuten |
| Hilfsmittel schriftlich | Lecture Notes (not including problems and solutions) and personal notes (max.4 pages). No electronic devices. (Pocket calculators will be handed out, if necessary.) |
| Diese Angaben können noch zu Semesterbeginn aktualisiert werden; verbindlich sind die Angaben auf dem Prüfungsplan. | |
Lernmaterialien
| Keine öffentlichen Lernmaterialien verfügbar. | |
| Es werden nur die öffentlichen Lernmaterialien aufgeführt. |
Gruppen
| Keine Informationen zu Gruppen vorhanden. |
Einschränkungen
| Keine zusätzlichen Belegungseinschränkungen vorhanden. |
Angeboten in
| Studiengang | Bereich | Typ | |
|---|---|---|---|
| Elektrotechnik und Informationstechnologie Master | Auflagen-Lerneinheiten | E- |  |