A wide range of research is carried out in the Electrical Systems and Applied Mathematics Research Division, covering various areas including electrics, communications, machines and applied mathematics. One of our main focuses is to invent and apply state of the art technologies, intelligence,computational and mathematical algorithms to various domains to improve current systems and processes for the benefit of mankind.
The domains we are currently pursuing are in the areas of renewable energy and automotive systems. We have in depth technical expertise and conduct research in the areas of audio-visual systems, wireless communications, optical communications, antennas, power electronics, machines and embedded systems.
Our main research groups in the division are:
Applied Electromagnetics and Communications
Research expertise within the Applied Electromagnetics and Communications Research Group includes equalisation and algorithm design and analysis, detection algorithm design and analysis, and matlab based simulations.
- Design and analysis of very efficient near-optimal equalisation and decoding algorithms for broadband wireless MIMO systems
- Reducing the computational complexity of TURBO codes
- Develop new detection algorithms that increase data throughput which are suitable for IEEE standards
- Design of fast convergence blind equalisation algorithms, for both single antenna as well as multiple-antenna systems
- Blind equalisation to eliminate the bandwidth-wasteful training sequence
- Novel combination of space-time-block-codes (STBC) and spatial multiplexing (SM) techniques to increase capacity or effective data throughput
- Simplifying TURBO decoding algorithm
- Design of novel near maximum-likelihood (ML) MIMO detection algorithms with much lower computational complexity than the optimal ML algorithm
The Applied Mathematics Research Group applies mathematical techniques to solve problems in various domains such as mathematics, physics and engineering. Members of our group are actively involved in research in quantum information, quantum field theory, probability and statistics, fractional calculus and asymptotic analysis.
- The Casimir effect
- Statistical analysis of non-parametric estimators
- The Kochen-Specker theorem
- Fractional integrations on discrete time scales
The common thread in the research activities of the Intelligent Systems Research Group is the use of intelligent systems for pattern recognition and machine learning in order to predict an outcome and/or decide on a suitable course of action in engineering and industrial processes. The inference engine used is the Support Vector Machine, a linear classifier with good generalisation capability.
- Pipeline riser defect prediction using Support Vector Machines
- SmartVehicle System to protect drivers and motor cyclists on Malaysian Roads (MOSTI)
- SVM based battery – Super-capacitor energy management system for Electric Vehicles (MOSTI)
- Detection and Prediction of Lung Cancer Using the zNose with the Support Vector Machine Classifier (MOSTI)
- Modelling and Analysis of Maglev Vertical Axis Wind Turbine
Power Electronics, Machines and Control
- Power electronics
- Energy conversion systems
- Renewable energy conditioning
- Regenerative braking/supercapacitor charge storage
- Energy management
- Electric machines and drives
- FACTS and HVDC systems
- Control systems; intelligent, robust, real-time with embedded systems