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Digital Signal Processing and Systems (ELEC0024)

Key information

Faculty
Faculty of Engineering Sciences
Teaching department
Electronic and Electrical Engineering
Credit value
15
Restrictions
N/A
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module provides students with an introduction to Digital Signal Processing and Signal classification. Students will explore sampled data systems, the z-transform, aliasing and the sampling theorem, analysis of random signals, digital filters, and multirate processing and adaptive filters. The aim of this module is to help students understand and apply mathematical and engineering principles and tools, to the analysis, performance assessment and evaluation of digital signal processing systems.

By the end of the module students should have a thorough understanding of:

  • Fourier analysis
  • Z transforms
  • Convolution
  • Probability & statistical analysis
  • Optimization methods
  • Application of Z transforms
  • Application of Fourier analysis
  • Communication channels
  • Noise in communications systems

    Module deliveries for 2024/25 academic year

    Intended teaching term: Term 2 ÌýÌýÌý Undergraduate (FHEQ Level 6)

    Teaching and assessment

    Mode of study
    In person
    Methods of assessment
    100% Exam
    Mark scheme
    Numeric Marks

    Other information

    Number of students on module in previous year
    31
    Module leader
    Professor Kit Wong
    Who to contact for more information
    eee-ug-admin@ucl.ac.uk

    Intended teaching term: Term 2 ÌýÌýÌý Undergraduate (FHEQ Level 7)

    Teaching and assessment

    Mode of study
    In person
    Methods of assessment
    100% Exam
    Mark scheme
    Numeric Marks

    Other information

    Number of students on module in previous year
    33
    Module leader
    Professor Kit Wong
    Who to contact for more information
    eee-ug-admin@ucl.ac.uk

    Last updated

    This module description was last updated on 8th April 2024.

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