A5007180550- Stability and Control of Uncertain Systems
- Control Systems and Identification
- Advanced Control Systems Optimization
- Fault Detection and Control Systems
- Adaptive Control of Nonlinear Systems
- Building Energy and Comfort Optimization
- Distributed Control Multi-Agent Systems
- Photonic and Optical Devices
- Target Tracking and Data Fusion in Sensor Networks
- Neural Networks Stability and Synchronization
- Machine Learning and ELM
- Neural Networks and Applications
- Stability and Controllability of Differential Equations
- Optical Network Technologies
- Model Reduction and Neural Networks
- Chaos control and synchronization
- Iterative Learning Control Systems
- Advanced Fiber Optic Sensors
- Advanced Photonic Communication Systems
- Matrix Theory and Algorithms
- Numerical Methods and Algorithms
- Advanced Adaptive Filtering Techniques
- Advanced Differential Equations and Dynamical Systems
- Numerical methods for differential equations
- Structural Health Monitoring Techniques
Nanyang Technological University
2013-2024
Agency for Science, Technology and Research
2012
Institute of Materials Research and Engineering
2012
National Grid (United States)
2010
Singapore Institute of Manufacturing Technology
2006
Nanyang Polytechnic
2004
University of Newcastle Australia
1985-2001
Nanyang Institute of Technology
2001
The University of Melbourne
1994
This paper is concerned with the problem of a Kalman filter design for uncertain discrete-time systems. The system under consideration subjected to time-varying norm-bounded parameter uncertainty in both state and output matrices. addressed linear such that variance filtering error guaranteed be within certain bound all admissible uncertainties. Furthermore, cost can optimized by appropriately searching scaling parameter.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) several limiting problems, such as variation signals drift PDR. An auxiliary tool for landmarks, which easily identified specific sensor patterns environment, this will exploited...
We consider distributed optimization problems in which a number of agents are to seek the optimum global objective function through merely local information sharing. The problem arises various application domains, such as resource allocation, sensor fusion and learning. In particular, we interested scenarios where use uncoordinated (different) constant stepsizes for optimization. According most existing works, using this kind stepsize rule update, is necessary asynchronous scenarios, will...
Human activity recognition using either wearable devices or smartphones can benefit various applications including healthcare, fitness, smart home, etc. Instead of which are intrusive and require extra cost, we shall leverage on modern embedded with a variety sensors. Due to the flexibility smartphones, accuracy will degrade orientation, placement, subject variations. In this paper, propose robust human system in terms variations based coordinate transformation principal component analysis...
We consider distributed optimization problems in which a number of agents are to seek the global optimum sum cost functions through only local information sharing. In this paper, we particularly interested scenarios, where operating asynchronously over stochastic networks subject random failures. Most existing algorithms require coordinated and decaying stepsizes ensure zero gap between estimated value each agent exact optimum, restricting it from asynchronous implementation resulting slower...
The Global Positioning System (GPS) can be readily used for outdoor localization, but GPS signals are degraded in indoor environments. How to develop a robust and accurate localization system is an emergent task. In this paper, we propose smartphone inertial sensor-based tracking with occasional iBeacon corrections. Some important issues smartphone-based pedestrian dead reckoning (PDR) approach, i.e., step detection, walking direction estimation, initial point studied. One problem of the PDR...
Some sufficient conditions for asymptotic stability of impulsive control systems with impulses at fixed times have recently been presented. In this paper, we derive some less conservative such and the results are used to design a class nonlinear systems. The considered is also extended.
This paper presents a novel rate control scheme for low delay video communication of H.264/AVC standard. A switched mean-absolute-difference (MAD) prediction is introduced to enhance the traditional temporal MAD model, which not suitable predicting abrupt fluctuations. Our new model could reduce error by up 69%. Furthermore, an accurate linear rate-quantization (R-Q) also formulated describe relationship between total amount bits both texture and nontexture information quantization parameter...
In this paper, adaptive filtering schemes are proposed for state estimation in sensor networks and/or networked control systems with mixed uncertainties of random measurement delays, packet dropouts and missing measurements. That is, all three the have certain probability occurrence network. The filter gains can be derived by solving a set recursive discrete-time Riccati equations. Examples presented to demonstrate applicability performances schemes.
Due to the complexity of H.264/AVC, it is very challenging apply this standard design a conversational video communication system. This problem addressed in paper by using region-of-interest (ROI) based bit allocation and computational power schemes. In our system, ROI first detected direct frame difference skin-tone information. Several coding parameters including quantization parameter, candidates for mode decision, number referencing frames, accuracy motion vectors search range estimation...
Open Cirrus is a cloud computing testbed that, unlike existing alternatives, federates distributed data centers. It aims to spur innovation in systems and applications research catalyze development of an open source service stack for the cloud.
Extreme learning machine (ELM) has recently attracted many researchers' interest due to its very fast speed, good generalization ability, and ease of implementation. It provides a unified solution that can be used directly solve regression, binary, multiclass classification problems. In this paper, we propose stacked ELMs (S-ELMs) is specially designed for solving large complex data The S-ELMs divides single ELM network into multiple small which are serially connected. approximate with...
This paper is concerned with solving a large category of convex optimization problems using group agents, each only being accessible to its individual cost function. The are modeled as minimizing the sum all agents' functions. communication process between agents described by sequence time-varying yet balanced directed graphs which assumed be uniformly strongly connected. Taking into account fact that channel bandwidth limited, for agent we introduce vector-valued quantizer finite...