Stability of a circuit with parasitic capacitances
A novel algorithm which is based on the linear programming technique is proposed to test the stability property of a circuit. This algorithm is efficient and non-Lyapunov equation based. Parasitic capacitances which may de-stabilize a circuit can be located.

title: Stability Analysis of RED Gateway with Multiple TCP Reno Connections
abstract: It has been observed that a bottleneck random early detection (RED) gateway becomes oscillatory when regulating a flow in multiple TCP connections. The stability boundary of the TCP-RED system depends on various network parameters, making the adjustment of the RED gateway a difficult task. Based on a fluid-flow model, analytical conditions were formulated that describe the stable boundary of the RED gateway depending on the number of TCP Reno connections. The proposed model accurately generates a stability boundary surface in a four dimensional space, which facilitates the adjustment of parameters for stable operation of the RED gateway. The accuracy of the analytical results has been verified using the ns-2 network simulations.

title: Fast analytical approach to finding steady-state waveforms for power electronics circuits using orthogonal polynomial basis functions
abstract: This paper describes a general analytical procedure for steady-state waveform analysis of power electronics circuits using orthogonal polynomials. The proposed method exploits the time-domain piecewise property of power electronics circuits as well as the orthogonality of certain polynomials in order to maximize the accuracy and computational efficiency. This new analytical approach can provide a fast means to obtain improved and more robust solutions of steady-state waveforms of power electronics circuits

title: Spurious modulation on current-mode controlled DC/DC converters: an explanation for intermittent chaotic operation
abstract: We explain the mechanism that causes "intermittent" instability and chaos in a current-mode controlled switching converter. The circuit model used to study the phenomenon incorporates a coupling process through which a spurious signal is coupled to the current sensing and ramp compensation circuitry, resulting in a modulation of the compensation slope which causes the system to become unstable intermittently. We describe a way to find the parameter boundaries where intermittent chaotic operation emerges.

title: Object Assisted Video Coding for Video Conferencing System
abstract: An object-based video coding for video conferencing system is proposed. There are two main processes: segmentation process and face detection process. The segmentation process is used to segment each frame of a video sequence into two non-overlapping regions, namely foreground and background. A novel face detection technique based on chrominance and the contour of the segmented region is applied to the foreground region. Smaller quantization step is used for the facial region to improve viewer's perception while a larger quantization step is used for the background to compensate the coding efficiency. The remaining regions are kept in normal coding quality to prevent degradation of important information other than the facial regio.

title: Optimum design of very low distortion class E power amplifiers
abstract: In this paper, the optimum design of a class E power amplifier with resonant tank being symmetrically driven by two class E circuits is studied. The optimally designed symmetrical class E circuit has extremely low harmonic distortion, and the load matching network (if required) is non-critical and can be designed with ease. Practical steady-state design equations are derived and graphically presented. Experimental circuits are constructed for distortion evaluation.

title: Robust Appearance-based Tracking using a sparse Bayesian classifier
abstract: An appearance-based approach to track an object that may undergo appearance change is proposed. Unlike recent methods that store a detailed representation of object's appearance, this method allows an appearance feature with a reduced dimension to be used. Through the use of a sparse Bayesian classifier, high classification and detection accuracy can be maintained even if a reduced feature vector is used. In addition, the classifier allows online-training which enables online-updating of the original classification model and provides better adaptability. Experiments show that the method can be used to track targets undergoing appearance change due to the change in view-point, facial expression and lighting direction

title: Real-Time Adaptive Hand Motion Recognition Using a Sparse Bayesian Classifier
abstract: An approach to increase adaptability of a recognition system, which can recognise 10 elementary gestures and be extended to sign language recognition, is proposed. In this work, recognition is done by firstly extracting a motion gradient orientation image from a raw video input and then classifying a feature vector generated from this image to one of the 10 gestures by a sparse Bayesian classifier. The classifier is designed in a way that it supports online incremental learning and it can be thus re-trained to increase its adaptability to an input captured under a new condition. Experiments show that the accuracy of the classifier can be boosted from less than 40% to over 80% by re-training it using 5 newly captured samples from each gesture class. Apart from having a better adaptability, the system can work reliably in real-time and give a probabilistic output that is useful in complex motion analysis.

title: Continuous Gesture Recognition using a Sparse Bayesian Classifier
abstract: An approach to recognise and segment 9 elementary gestures from a video input is proposed and it can be applied to continuous sign recognition. An isolated gesture is recognised by first converting a portion of video into a motion gradient orientation image and then classifying it into one of the 9 gestures by a sparse Bayesian classifier. The portion of video used is decided by using a sampling technique based on condensation framework. By doing so, gestures can be segmented from the video in a probabilistic manner. Experiments show that the proposed method can achieve accuracy around 90% in both isolated and continuous gesture recognition without using special equipment such as glove devices and the system can run in real-time

title: Development of Hybrid Optimisation Techniques Based on Genetic Algorithms and Simulated Annealing

title: Design patterns for games
abstract: Designing a two-person game involves identifying the game model to compute the best moves, the user interface (the "view") to play the game, and the controller to coordinate the model and the view. A crucial task is to represent the algorithms used in their highest abstract forms. This can prove to be a difficult and subtle endeavor. It is made easier however by the use of good object-oriented (OO) design principles to help maintain a high level abstract viewpoint during the design process. The state pattern is used to represent the game board and is coupled with the visitor pattern to provide state-dependent, variant behaviors. The min-max algorithm and its variants are implemented as the strategy pattern, which allows flexible and extensible computational capability. Careful analysis is performed to properly abstract the interactions between the model and the view. The command design pattern is used to provide callback services between the model and the view. Leading students through this design process enables them to learn algorithms and architectures that easily scale to full-sized applications.