Coursework - Group Report
A 2500-word group report on the design and evaluation of digital signal, information, and data processing solutions for real-world problems. Learners will use appropriate simulation and data analysis tools to assess system performance in terms of accuracy, efficiency, robustness and relevant sustainability and ethical considerations, weighted at 50%, meeting Learning Outcomes 3 and 4. Assessing AHEP 4 Outcomes: C3, C4, C5, C6, C12.

Examination
A 1.5-hour exam requiring theoretical and calculations-based questions on digital signal, information and data processing to be answered, weighted at 50% meeting Learning Outcomes 1 and 2. Assessing AHEP 4 Outcomes: C1, C2, C3.

This module provides a comprehensive understanding of digital signal, Information and Data Processing, covering theoretical concepts and practical applications. Students will learn to analyse signals and extract information from data, with hands-on labs using MATLAB and DSP hardware.

The module will cover the following topics:
- Information Extraction & Feature Engineering: Information theory (entropy, mutual information) for quantifying signal informativeness; feature selection criteria. Time-domain feature extraction and frequency-domain feature extraction using Python.
- Data Processing & Analysis: Data preprocessing pipelines, statistical inference for signal quality assessment.
- Pattern Recognition & Machine Learning Integration: Supervised/unsupervised learning basics for signal classification; model evaluation metrics.
- System Design & Real-Time Implementation: Real-time signal processing constraints (latency, computational complexity); hardware-software co-design principles; Implementing a digital filter on a DSP processor; Designing an FPGA-based signal acquisition system with VHDL.

1. Demonstrate a well-developed understanding of digital signal processing, information theory and data processing concepts, including system-level design principles. (AHEP 4: C1, C2)

Learning Outcome: Knowledge & understanding

2. Critically analyse digital signal, information and data processing methods, including the justification of design choices. (AHEP 4: C2, C3)

Learning Outcome: Application & problem-solving

3. Design digital signal, information and data processing solutions for real-world problems, including feature extraction and interpretation of signal characteristics. (AHEP 4: C3, C5, C6)

Learning Outcome: Application & problem-solving

4. Use simulation and data analysis tools to collaboratively evaluate the performance of signal, information and data processing systems in terms of accuracy, efficiency, robustness and relevant sustainability and ethical considerations. (AHEP 4: C4, C6, C12)

Learning Outcome: Digital literacy, Critical reasoning & collaboration

Whole group lectures will be used to deliver new material and to consolidate previous material. Small-group tutorials, with activities designed to enhance the understanding of the material delivered in the lectures, will be used to apply the skills and knowledge learned. A mixture of classroom based, and practical activities will take place supported by staff.

Suitable simulation tools such as MATLAB, Python programming environment, or equivalent.
Suitable hardware resources for practical sessions.

Must be registered on BEng (Hons) Electronic and Information Engineering provision at XUPT, China.

Figueiredo, T. and Rogers, R. (2025) Digital Signal Processing: Principles, Algorithms and Applications. UK: Kruger Brentt Publisher Ltd.

McKinney, W. (2022) Python for Data Analysis. 3rd edn. Sebastopol, CA: O'Reilly Media.

Proakis, J.G. (2013) Digital Signal Processing: Principles, Algorithms and Applications. Boston, MA: Pearson.

Sundararajan, D. (2024) Digital Signal Processing: An Introduction. 2nd edn. Cham: Springer.

This module focuses on advanced topics in information extraction, data processing, and machine learning integration. Students will learn to extract meaningful features from signals, analyse complex data using statistical methods, and design real-time systems for practical applications.