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Higher Education Technical Challenges Hub: Module Specification

ICT10M2 Digital Signal Processing

pdf version of module specification

Download the module specification

pdf version of module specification








Module name:

Digital Signal Processing

Scope and form:

Lectures and group exercises in connection with the lectures.

Duration (weeks; Hours/week):

15 weeks; 4 h/week

Type of assessment:

Distributed evaluation with final exam. Practical classes based on the lectures

Qualified Prerequisites:

Basics in calculus, algebra, computer sciences

General module objectives:

The objective of this module is to introduce students studying electronics, computer and biomedical engineering to the fundamental principles of DSP and to provide a working knowledge such that they can apply DSP in their engineering careers

Topics and short description:

Basic concepts of digital signal processing. Signal sampling and quantization. Analog-to-digital and digital-to analog convertors. Digital signal processing applications.
Digital signal processors. Von Neumann and Harvard architecture. Main hardware units. Fixed point and floating point formats.
Discrete Fourier transform and signal spectrum. Application to signal spectrum estimation. Fast Fourier transform. The z-transform and its properties. Inverse z-transform.
Noise and distortion. Types of noise. Noise modelling. Basic filtering types and digital filter realizations. Difference equation and transfer function. Moving average filters, window-sinc filters, Chebyshev filters.
Wavelet basics and families of wavelets. Discrete wavelet transform.
Implementation of basic functions in MATLAB.

Learning outcomes:




The basic concepts of digital signal processing

Able to select  DSP processor appropriate for a given problem  

Able to review the overall picture of DSP applications

The fundamentals of DSP transforms and filtering

Implementation of algorithms for main methods of filtration and transforms

Able to comprehend the applicability of filtration to different types of signals

The fundamentals of wavelet transforms

To design and implement algorithms of wavelet transforms with different basic wavelets

Students have to be able to select and implement an appropriate method

Recommended literature:

L. Tan. Digital signal processing fundamentals and application. Elsevier, 2008.
S. Vaseghi. Advanced Digital Signal Processing and Noise Reduction, Wiley, 2006.
 Steven W. Smith. The Scientist and Engineer's Guide to Digital Signal Processing .
V. Ingle, J. Proakis. Digital signal processing using MATLAB, 1997.
DSP — MATLAB and Simulink solutions.