Digital Signal Processing

Code

IT-DSP1

Version

2.0

Offered by

ICT Engineering

ECTS

Prerequisites

Upper level mathematics equivalent to A-levels

Main purpose

The purpose of the course is to equip the student with basic knowledge about the fundamentals of Digital Signal Processing and its applications.

Starting from the basic definition of a discrete-time signal, we will work our way through sampling, filter design, and Fourier analysis to build a basic DSP toolset. Signal processing is one of the fundamental theories and techniques to construct modern information systems. For example, audio, speech, and image processing, computer graphics, biomedicine all apply digital signal processing. In fact, digital signal processing is used to develop algorithms that can diagnose heart disease and can even be used to detect hostile drones. The course familiarizes the student with digital signals, sampling theory, digital filtering, the Fast Fourier Transform, power spectrum, and feature extraction.

Knowledge

After successfully completing the course, the student will have gained knowledge about:

• The nature and recording of different types of digital signals
• Cleaning up digital signals
• Extracting useful values from digital signals
• MATLAB as a tool for development of signal processing algorithms

Skills

After successfully completing the course, the student will be able to:

• Record digital signals
• Applying different filters (high-pass, low-pass, band-pass, notch) to remove unwanted components of digital signals
• Use the Fast Fourier Transform to analyze the frequency content of a signal

Competences

After successfully completing the course, the student will have acquired competences in:

• Explain sampling processes and how to determine the correct sampling frequency
• Describe signal processing applications
• Applying digital signal processing methods to analyze and interpret engineering problems
• Develop signal processing algorithms

Topics

Teaching methods and study activities

Approximately 150 hours.

The course is a mixture of lectures, hands-on MATLAB exercises, and hand-ins with approximately 1/3 of the time devoted to each part. Exercises are carried out in teams of 2-3 students.

Resources

Mark Owen - Practical Signal Processing © Cambridge University Press (ISBN 978-1-107-41182-1)
The MATLAB software will be integrated into this course.

Evaluation

Examination

Exam prerequisites:
None

Exam type:
Individual oral exam, 20 min.
Exam is based upon an assignment handed in before deadline.
The students will present the assignment in the form of a demonstration, followed by questions about the signal processing and feature extraction methods as well as the MATLAB programming.
Internal assessment.

Tools allowed:
N/A

Re-exam:
Same as the ordinary exam (new assignment).

Grading criteria

Grading based on the Danish 7 point scale.

Additional information

Responsible

Line Lindhardt Egsgaard (lile)

Valid from

2/1/2024 12:00:00 AM

Course type

6. semester
7. semester
Elective for the specialization Internet of Things
Electives
Web 6 og 7

Keywords

What is a signal?, MATLAB, Sampling theory, A/D conversion, Digital filters, The frequency domain, The Fast Fourier Transform and power spectrum, Feature extraction (RMS, AUC, peak detection, peak latency, peak to peak, time intervals)