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- At least a good relevant bachelor's degree
- Relevant working experience is an advantage
- For applicants whose native language is not English, TOEFL/IELTS score is to be submitted with the application for admission:
TOEFL Score (Test dates must be within 2 years or less from the date of application):
≥ 600 (paper-based)
≥ 250 (computer-based)
≥ 100 (internet-based)
IELTS Score (Test date must be within 2 years or less from the date of application):
≥ 6.5
Programme Structure
There are two options of study, one with coursework and dissertation, and the other with coursework only. Each course is of 3 AUs and consists of 39 hours of lectures. Candidates who undertake a project of 6 AUs must submit a dissertation on it.
Option 1 | Option 2 |
| 8 courses + dissertation project (30 AUs in total) | 10 courses (30 AUs in total) |
| 4 specialized electives (≥ 12 AUs) | 4 specialized electives ((≥ 12 AUs) |
| 4 specialized electives (≤ 12 AUs) | 6 specialized electives (≤ 18 AUs) |
| Dissertation (6 AUs) |
Full-time students are strongly recommended to select the dissertation option, however this option is recommended only for students with a high level of English proficiency. Students taking the dissertation option may take a longer time to complete the programme.
Note: The programme structure will be subject to change without prior notice.
Duration
Both full-time and part-time programmes are offered (unless stated). Part-time candidates are expected to obtain permission from their employer before admission to the programme. All classes are conducted in the evenings, while ex aminations are conducted during office hours.
Type of Coursework Programme | Minimum Candidature | Maximum Candidature |
Master of Science (Full-Time) | 1 year | 3 year |
Master of Science (Part-Time) | 2 year | 4 year |
Programme Calendar
| Semester 1 | August to December |
| Semester 2 | January to May |
| Week 1 to 14 | Lecture (Inclusive of 1-week recess) |
| Week 15 to 17 | Examinations |
| Other | Vacation |
Graduate courses offered by Master of Science (MSc) Signal Processing:
Specialized Elective Courses (Students are required to take a min of 4 out of all the 5 specialized elective courses)
Course Code | Course Title | Course Content | AUs |
| EE6101 | Digital Communication Systems | Communication signals and baseband transmission. Digital modulation/demodulation. Error correction coding. Spread-spectrum techniques. | 3 |
| EE6401 | Advanced Digital Signal Processing | Discrete signal analysis and digital filters. Power spectrum estimation. Linear prediction and optimal linear filters. Multi-rate digital signal processing. DSP Architectures and applications. | 3 |
| EE6402 | Real-time DSP Design and Applications | Digital Filter Implementation Issues. Advanced Arithmetic Techniques for Hardware. Architecture for General Purpose Digital Signal Processor. Peripherals for DSP Applications. Design and Development Tools for DSP Processors. Introduction to VLSI. Algorithms and Architecture for VLSI. | 3 |
| EE6403 | Distributed Multimedia Systems | Media and Media Systems. Media Compression and Standards. Media Processing and Storage. Media Transmission and Delivery. Quality of Service on Distributed Multimedia Systems. Multimedia Applications. | 3 |
| EE6427 | Video Signal Processing | Image and Video Basics. Image and Video Transform Coding. Filtering and Error Resilience for Image and Video. Image and Video Coding Principles and Standards. Recent and Emerging Topics in Image and Video Processing. | 3 |
General Elective Courses
Course Code | Course Title | Course Content | AUs |
| EE6010 | Project Management & Technopreneurship | project Initiation and Planning. Project Scheduling and Implementation. Project Monitoring, Control and Evaluation. Innovation and Entrepreneurship. | 3 |
| EE6129 | Wireless & Mobile Radio Systems | Wireless channel models. Fading and ISI mitigation techniques. Cellular concept and Multiple access techniques. Satellite communications. | 3 |
| EE6204 | Systems Analysis | Linear, Dynamic and Integer Programming. Optimization Techniques. Random Processes. Queuing Models. Markov Decision Process. | 3 |
| EE6222 | Machine Vision | Fundamentals of image processing & analysis. Feature Extraction Techniques. Pattern / Object Recognition and Interpretation. Three- Dimensional Computer Vision. Three-Dimensional Recognition Techniques. Biometrics. | 3 |
| EE6227 | Genetic Algorithms and Machine Learning | Review of Combinatorics and Probability. Introduction of Genetic Algorithms. Differential Evolution. Particle Swarm Optimization. Advanced Techniques. Principles of Machine Learning. Paradigms of Machine Learning. Kernel Methods. | 3 |
| EE7207 | Neural and Fuzzy Systems | Introduction to artificial neural networks. Recurrent and Hopfield Neural Network. Multi-layer perception neural network. Radial basis function neural network. Support vector machines. Self-organizing map neural network. Applications of neural network. Fundamentals of fuzzy logic and fuzzy systems. Takagi-Sugeno (T-S) fuzzy modelling and identification. Stability analysis of fuzzy systems. Applications of fuzzy systems. | 3 |
| EE7401 | Probability and Random Processes | Probability concepts. Random variables. Multiple random variables. Sum of random variables and multidimensional distributions. Random Sequences. Probability density function estimation. Random variable simulation. Random processes. Correlation functions. Spectral density. Random processes | 3 |
| EE7402 | Statistical Signal Processing | Signal Estimation Theory. Properties of Estimators. Fundamentals of Detection Theory. Detection of Deterministic and Random Signals. Application of Signal Detection and Estimation. Introduction to Adaptive Filtering. Gradient based Adaptation. Adaptive Filter Applications. | 3 |
| EE7403 | Image Analysis and Pattern Recognition | Image Fundamentals. Image Enhancement and Restoration. Image Analysis. Decision Theory and Statistical Estimation. Classification and Clustering. Dimensionality Reduction. | 3 |
Note: the above curriculum is subject to change.
Tuition Fee
Five MSc programmes (Communications Engineering, Computer Control & Automation, Electronics, Power Engineering and Signal Processing) are self-financed programmes.
Students of this programme are not eligible for Service Obligation/ MOE Subsidies.
The tuition fees per module (3 AUs) and per dissertation (6 AUs) for admission AY2020 onwards are shown in the tables as follows:
| Admission Year | Singaporeans (SC) | Singapore PRs (SPR) | International Students (IS) | |||
|---|---|---|---|---|---|---|
| (Per Module) | (Per Dissertation)^ | (Per Module) | (Per Dissertation)^ | (Per Module) | (Per Dissertation)^ | |
AY2020-2021 onwards | S$3,000* | S$6,000* | S$3,500* | S$7,000* | S$4,000* | S$8,000* |
Total Programme Fee (Minimum) | Total Programme Fee (Minimum) |
Total Programme Fee | ||||
| S$30,000 | S$35,000 | S$40,000 | ||||
*Exclusive of GST
^The tuition fee for Dissertation (6 AUs) will be twice of each module fee.
All fees listed above are in Singapore dollars (S$), and subject to annual revision by the school.
The tuition fee is exclusive of living expenses and miscellaneous student fees
The deposit fee S$2,000 is payable upon acceptance of offer and non-refundable. It will be deductible from the full tuition fee.
Payment schedule for semester 1 and semester 2 is in September and February respectively.