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Teaching Responsibility

LJMU Schools involved in Delivery:

LJMU Partner Taught

Learning Methods

Lecture

Practical

Module Offerings

4605ICBTEL-AUG-PAR

4605ICBTEL-SEP-PAR

4605ICBTEL-SEP_NS-PAR

Aims

This module will introduce basics of Signals and Systems. In addition, Students will be exposed to artificial intelligence and software packages.

Learning Outcomes

1.
Understand and apply of the basic concepts of signals and systems
2.
Solve mathematical problems related to signals and systems
3.
Use computer software for design and development of signals and systems with AI
4.
Apply primary and secondary research methods to improve signals and systems techniques with AI and communicate findings

Module Content

Outline Syllabus:
 
  1. Introduction to signals and systems
  2. Mathematical modelling of CT systems
  3. First order and second order CT transfer function for physical systems.
  4. CT second order time response. (Step response)
  5. DT system blocks and DT transfer function.
  6. DT convolution graphical method
  7. DT Impulse response
  8. Fourier series
  9. Fourier transform
  10. DFT / 2D DFT / DCT / Hadamard transform / Haar transform / Wavelet transform
  11. CT and DT signal plotting and shifting
  12. Plot signals using relevant software’s (Example – Matlab).
  13. Programming for AI
  14. Introduction to machine learning
  15. Introduction to data cleaning and feature engineering
  16. Introduction to computer vision
  17. Introduction to natural language processing
  18. Introduction to Time Series Analysis
  19. Introduction to recommender systems
  20. Demonstrate case studies of AI using relevant programming and resources.    

 
Module Overview:
 

This module aim is to provide a good understanding of signals and systems with AI for practical applications.
Additional Information:
This module provides a theoretical and practical learning experience of signals and systems with AI for practical applications.

Assessments

Exam

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