Communication and Media Engineering

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EMI Department

Module Guide

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Advanced Digital Signal Processing

Prerequisite

Advanced DSP lecture
Teaching methods Lecture/Lab
Learning target / Competences

Understanding the fundamental theoretical tools for analysis of most relevant DSP problems and ability to apply them in practice with Matlab
Duration 2
Hours per week 5.0
Overview
Classes 75 h
Individual / Group work: 105 h
Workload 180 h
ECTS 5.0
Requirements for awarding credit points

Advanced Digit. Signal Processing: written exam K90

DSP Lab must be passed.
Responsible person

Prof. Dr. Christian Reich
Frequency Annually (ss)
Usability

Master's degree program CME
Lectures

Advanced Digit. Signal Proc.

Type Lecture
Nr. EMI414
Hours per week 4.0
Content
  • Transform Analysis of Linear Time-Invariant Systems: Frequency Response Components, All-Pass Filters, Minimum-Phase Systems.
  • IIR Filter Design: Approximation of Differential Equation, Impulse and Step Invariance Design, Bilinear Transformation.
  • IIR Filter Structures: Noncanonical and Canonical Direct Form, Transposed Direct Form, Parallel Form, Cascade Form. Finite Precision Numerical Effects.
  • FIR Filter Design Techniques: Fourier Approximation, Windowing, Optimum Equiripple Approximation.
  • Discrete Fourier Transform (DFT): Linear and Circular Convolution, Fast Fourier Transform (FFT) Algorithms.
  • Multirate Processing: Downsampling, Decimation Filter, Upsampling, Interpolation Filter.
  • Adaptive Signal Processing: Configuration in different Applications, Optimum Filter, Least-Mean-Squares Algorithm.
Literature

Oppenheim, Alan V.; Schafer, Ronald W.: Discrete-Time Signal Processing. Pearson, 2013.

Digita Signal Processing Lab Work

Type Lab
Nr. EMI415
Hours per week 1.0
Content

Experiment 1: Matlab Onboarding
- Design of an amplitude modulation system in Matlab
- Visualization of effects of its modules
- Description of effects of its modules

Experiment 2: Infinite Impulse Response (IIR-) Filters
- Analysis of IIR filters
- Approximation methods for time-continuous filter (Butterworth, Chebyshev, Elliptic)
- Filter design using the Bilinear Transform with Matlab Filter Designer (lowpass and bandpass filters)

Experiment 3: Finite Impulse Response (FIR-) Filters
- Filter Design Using the Fourier Approximation
- Modification by Using Window Functions
- Optimum Design (Parks-McClellan-Algorithm)
- Finite Precision Effects
- Design of Hilbert Filters (Wideband Phase Shifters)
Literature

User guides for experiments are provided
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