Teaching Responsibility
LJMU Schools involved in Delivery:
LJMU Partner Taught
Learning Methods
Lecture
Practical
Tutorial
Module Offerings
7550WCSST-SEP-PAR
Aims
This module aims to develop an advanced understanding of techniques and practical experience in applications of digital signal processing (DSP).
Learning Outcomes
1.
Analyse advanced concepts and analytical tools for DSP systems
2.
Design and implement a range of complex digital filters
3.
Apply high level techniques for a stochastic signal
4.
Use DSP to implement a range of complex engineering applications
Module Content
Outline Syllabus:Digital Signal Processing (DSP) and Systems – Fundamentals, Architectures and
Characteristics
Analysis Tools and Transforms – Fourier: Continuous Time Fourier Transform
(CTFT), Discrete Time Fourier Transform (DTFT), Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT); Laplace and Z-transforms
Digital Filters: Design and Implementation – Finite Impulse Response (FIR), Infinite Impulse Response (IIR), Analogue Prototypes & Algorithms
A/D and D/A Conversions – Quantization, Sample and Hold, Antialiasing, Acquisition
Speech Processing – Linear predictive coding (LPC), Synthesis, Coding and Recognition
DSP Hardware Architecture
Efficient Implementation of DSP algorithms on Hardware
Stochastic signal processing, Random Processes, Spectrum, Power Spectral Density (PSD), white noise
Additional Information:This module aims to develop an advanced understanding of techniques and practical experience in industry-oriented applications of digital signal processing.
United Nations Sustainable Development Goals:
3. Good Health and Wellbeing
7. Affordable and Clean Energy
9. Industry, Innovation and Infrastructure
11. Sustainable Cities and Communities
12. Responsible Consumption and Production
Assessments
Report
Exam