EEEN30050 Signal Processing: Theory and Applications

Academic Year 2023/2024

This module covers the theoretical basis of discrete-time signal processing (digital signal processing), and gives practical applications of DSP such as signal filtering, signal interpretation, and signal analysis. DSP is widely used in digital communications, digital media, and computational science and this course provides the framework for applications in electronic engineering, computer science, physics, geology and applied mathematics.

Specific topics covered include discrete Fourier transforms, fast Fourier transform, z-transforms, linear time invariant systems, digital filtering, and digital filter (FIR and IIR) design. A number of computer based assignments are given. Both Matlab and Python are used to demonstrate the theories.

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Curricular information is subject to change

Learning Outcomes:

Please note that the codes given at the end of each Learning Outcome relate to the Programme Outcomes specified by Engineers Ireland for the professional accreditation of degree programmes.

On successful completion of this module a student should be able to:

. Calculate the necessary properties of a sampled signal to accurately represent information. [PO(A), 4]; [PO(B), 4]; [PO(C), 4]

. Demonstrate understanding of the links between analogue and digital transforms. [PO(A), 4]

. Derive efficient computational schemes for the Discrete Fourier Transform. [PO(A), 4]; [PO(B), 4]; [PO(C), 4]

. Use the z-transform to analyse discrete signals and systems. [PO(A), 4]; [PO(B), 4]

. Design digital filters to meet various types of specification. [PO(A), 4]; [PO(B), 4]

Indicative Module Content:

The following topics will be covered:

- Sampling theorem and signal reconstruction

- Development of Discrete Fourier Transform

- Fast Fourier Transform

- Discrete Convolution

- z-transform

- Digital systems

- FIR and IIR filter design

Student Effort Hours: 
Student Effort Type Hours
Specified Learning Activities


Autonomous Student Learning






Approaches to Teaching and Learning:
- lectures, practicals, tutorials,

- lab work

- problem-based learning 
Requirements, Exclusions and Recommendations
Learning Requirements:

Signals, Systems and Control (EEEN30010) or equivalent. This course is mathematically challenging, so a strong background in university honours level mathematics in the areas of linear algebra, calculus, and transforms is required.

Module Requisites and Incompatibles
EEEN30110 - Signals & Systems

Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Class Test: Mid-term in-class test Week 7 n/a Standard conversion grade scale 40% No


Examination: Terminal written examination 2 hour End of Trimester Exam No Standard conversion grade scale 40% No


Assignment: Signal processing exercises Week 10 n/a Graded No


Lab Report: 3 lab reports Varies over the Trimester n/a Graded No


Carry forward of passed components
Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

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Digital Signal Processing by Proakis and Manolakis
Discrete time Signal Processing by Oppenheim
Name Role
Assoc Professor Nam Tran Lecturer / Co-Lecturer
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Lecture Offering 1 Week(s) - 20, 21, 22, 26, 31 Fri 11:00 - 12:50
Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 15:00 - 16:50
Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 14:00 - 14:50