Digital Signal Processing

Learning Outcomes

Students upon completion of the course will have gained a good understanding and knowledge of the main ideas, algorithms, and tools in the area of ​​digital signal processing and will be able to:

• Implement sampling of continuous time signals and reconstruct them from their samples by choosing appropriate parameters and functions.
• Change the sampling rate of discrete-time signals, avoiding folding effects.
• Recognize the basic signals and categories of discrete-time systems.
• Analyze signals and systems in the discrete time domain.
• Compute the frequency response of linear and time-invariant discrete-time systems, implement decomposition into a minimum-phase system and an all-pass system, and describe generalized linear-phase systems.
• Implement discrete-time systems using various structures.
• Design filters with an infinite or finite impulse response using appropriate methods.
• Understand the importance of the discrete Fourier transform and algorithms for its fast computation.
• Analyze discrete-time signals in the frequency domain, using the windowing method as well as the time-dependent discrete Fourier transform, and reconstruct the signal with the overlap-sum algorithm.
• Analyze and implement systems in the field of Z transformation.
• Understand and/or implement code in the Matlab computing environment to achieve the above.

Indicative Module Content

• Introduction to Digital Signal Processing
• Discrete-time Signals
• Discrete-time Systems
• Discrete Fourier Transform and applications
• Frequency response
• Frequency Domain Representation of Discrete-time LTI Systems
• Analog to digital conversion
• Z-transform
• Digital filter Design