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

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