t.BA.XX.DSV1.19HS (Digital Signal Processing 1) 
Module: Digital Signal Processing 1
This information was generated on: 29 November 2022
No.
t.BA.XX.DSV1.19HS
Title
Digital Signal Processing 1
Organised by
T ISC
Credits
4

Description

Version: 2.0 start 01 August 2020
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Short description

The DSV1 module covers the basics of digital signal processing and teaches students the most important algorithms. The algorithms are partly designed and analysed in MATLAB to this end and are implemented and measured on a microcontroller/DSP (e.g. STM32F769).

Module coordinator

Wyrsch Sigi, wyrs

Learning objectives (competencies)

Objectives Competences Taxonomy levels
The students understand the basics of Digital Signal Processing (DSV). F, M K2-K4
(1) You can use Matlab/Python to analyze and implement DSV algorithms and design filters. F, M K3-K5
(2) You understand simple DSV applications. F K2
(3) You can program small real-time applications on a digital signal processor (MCU or DSP) in C. F K3-K5

Module contents

- AD-DA conversion (sampling, reconstruction, quantization, undersampling, aperture and clock sampling jitter (phase noise), DDS technology)
- DFT and FFT
(DFT and properties, FFT algorithm, FFT of real signals, leakage, windowing, zero padding, frequency inversion, spectrograms)
- Digital systems
(difference equation, z-UTF, convolution, correlation, realization structures, fixed-point realization)
- FIR and IIR filter design
(Filter specification, FIR filter design with windowing, with frequency sampling and in the z-range, IIR filter design with analog prototype filters with bilinear transformation and in the z-range)
-Conversion of the algorithms in C to MCU (STM32F769 MCU) or to Fixed-Point DSP TMS320VC5510 from TI
-DSV Tips & Tricks (Filter Sharpening, Cordic Algorithm, Amount (Abs) Approximation, Spectral Peak Location Estimation (FFT Peak Interpolation, Zero-Phase Filtering, Time-Domain Windowing in the Frequency Domain, Efficient Multiplication of two complex numbers, DC Removal Filter)
-Overview of special FIR filters (IFIR filters, overlaps save alogrithm)

Teaching materials

Script, slides, practical courses and exercises all with sample solutions

Supplementary literature

Book from ZHAW library (pdf): "Applied Digital Signal Processing" by Dimitris Manolakiy and Vinay Ingle

Prerequisites

Fourier series and Fourier transform, basic knowledge of programming and the use of MATLAB/Phyton

Teaching language

(X) German ( ) English

Part of International Profile

( ) Yes (X) No

Module structure

Type 3a
  For more details please click on this link: T_CL_Modulauspraegungen_SM2025

Exams

Description Type Form Scope Grade Weighting
Graded assignments during teaching semester Exam written each about 50 min. Mark; 1 to 6 2 x 20%
End-of-semester exam Exam written 90 min. Mark; 1 to 6 60%

Remarks

 

Legal basis

The module description is part of the legal basis in addition to the general academic regulations. It is binding. During the first week of the semester a written and communicated supplement can specify the module description in more detail.
Course: Digitale Signalverarbeitung 1 - Praktikum
No.
t.BA.XX.DSV1.19HS.P
Title
Digitale Signalverarbeitung 1 - Praktikum

Note

  • No module description is available in the system for the cut-off date of 01 August 2099.
Course: Digitale Signalverarbeitung 1 - Vorlesung
No.
t.BA.XX.DSV1.19HS.V
Title
Digitale Signalverarbeitung 1 - Vorlesung

Note

  • No module description is available in the system for the cut-off date of 01 August 2099.