[Truncated abstract] Genetic algorithms (GAs) have been extensively used and studied in computer science, yet there is no generally accepted methodology for exploring which parameters significantly affect performance, whether there is any interaction between parameters and how performance varies with respect to changes in parameters. This thesis presents a rigorous yet practical statistical methodology for the exploratory study of GAs. This methodology addresses the issues of experimental design, blocking, power and response curve analysis. It details how statistical analysis may assist the investigator along the exploratory pathway. The statistical methodology is demonstrated in this thesis using a number of case studies with a classical genetic algorithm with one-point crossover and bit-replacement mutation. In doing so we answer a number of questions about the relationship between the performance of the GA and the operators and encoding used. The methodology is suitable, however, to be applied to other adaptive optimization algorithms not treated in this thesis. In the first instance, as an initial demonstration of our methodology, we describe case studies using four standard test functions. It is found that the effect upon performance of crossover is predominantly linear while the effect of mutation is predominantly quadratic. Higher order effects are noted but contribute less to overall behaviour. In the case of crossover both positive and negative gradients are found which suggests using rates as high as possible for some problems while possibly excluding it for others. .... This is illustrated by showing how the use of Gray codes impedes the performance on a lower modality test function compared with a higher modality test function. Computer animation is then used to illustrate the actual mechanism by which this occurs. Fourthly, the traditional concept of a GA is that of selection, crossover and mutation. However, a limited amount of data from the literature has suggested that the niche for the beneficial effect of crossover upon GA performance may be smaller than has traditionally been held. Based upon previous results on not-linear-separable problems an exploration is made by comparing two test problem suites, one comprising non-rotated functions and the other comprising the same functions rotated by 45 degrees in the solution space rendering them not-linear-separable. It is shown that for the difficult rotated functions the crossover operator is detrimental to the performance of the GA. It is conjectured that what makes a problem difficult for the GA is complex and involves factors such as the degree of optimization at local minima due to crossover, the bias associated with the mutation operator and the Hamming Distances present in the individual problems due to the encoding. Furthermore, the GA was tested on a real world landscape minimization problem to see if the results obtained would match those from the difficult rotated functions. It is demonstrated that they match and that the features which make certain of the test functions difficult are also present in the real world problem. Overall, the proposed methodology is found to be an effective tool for revealing relationships between a randomized optimization algorithm and its encoding and parameters that are difficult to establish from more ad-hoc experimental studies alone.

This thesis explores moving information processing by means of quantum computation technology via neural networks. A new quantum computation algorithm achieves a double-accurate outcome on measuring optical flows in a video. A set of neural networks act as experimental tools that manipulate the applied data. Attempts have been made to calculate a pixel's location, velocity and grey scale value of moving images but the location and velocity could not be simultaneously measured precisely enough in accordance with both classical and quantum uncertainty principles. The error in measurement produced by quantum principles was found to be half that produced by a classical approach. In some circumstances the ratio of a pixel's coordinates and that of velocities could be determined using quantum eigenstate theory. The Hamiltonian of interaction of two NOT gates is most likely to represent the Gibbs potential distribution in calculating the posterior probability of an image. A quantum chain code algorithm was erected to describe the edges of image features. The FACEFLOW experimental system was built in order to classify the moving human faces. Three kinds of neural network models were finally presented. / Doctor of Philosophy (PhD)

Almost all recent microprocessors and DSP chips perform addition, subtraction, multiplication and division in hardware. However, studying their performance reveals that division is not carried out as fast as the other three operations. One investigation shows that while floating-point division, with about 3 % of the dynamic floating - point instruction count, seems to be a relatively unimportant instruction, it may cause about 40 % degradation to the overall system performance. Several mathematical algorithms have been developed over the past 50 years to perform division quickly, with high precision. However, only a few are suitable for implementation in VLSI. Among them, digit recurrence algorithms are the most widely accepted methods of performing floating - point division in the latest processors. A survey shows that out of 13 recent processors, 11 use SRT division ¹ for performing floating - point division. Investigations show that SRT division gives the best tradeoff between delay and area. Selecting SRT division for implementing floating - point division is a reasonable choice because, unlike the other class of division algorithms, i.e. functional, it produces a correctly rounded quotient conforming to the IEEE 754 standard. There are techniques for improving the performance of SRT division. Of these, increasing the speed of quotient digit selection ( QDS ), making the best balance between the radix and the redundancy factor, representing the partial remainder in a redundant form, converting the quotient from redundant to conventional form the on - the - fly and overlapping the division recurrence components are the most important. In this thesis a different method of implementing the QDS function is proposed. This approach, which is described mathematically and architecturally, is based on the new comparison multiples idea. Unlike the traditional implementation of the QDS function, which searches for the quotient digit in a lookup table, the proposed method calculates the quotient digit directly in sign and magnitude format. This approach almost halves the fan out of some critical path components, which therefore operate faster. Having received the truncated partial remainder, the QDS function compares it with truncated multiples of the divisor to find the range in which the partial remainder belongs. The results of the comparisons are converted to the magnitude of the quotient digit using simple logic called the coder. Concurrently, another circuit checks the truncated partial remainder to determine whether the quotient digit is negative. This circuit operates off the critical path since the comparison multiples based QDS function calculates the sign and magnitude of the quotient digit separately. Having applied these changes, a faster QDS function and consequently, a shorter critical path delay for the floating - point divider is obtained. Implementations of radix - 4 and radix - 16 floating - point dividers are investigated and optimised to further decrease the cycle time. The idea of comparison multiples is extended to radix 10 to implement a decimal floating - point divider complying with the IEEE 754R standard. To achieve this goal, decimal signed - digit arithmetic along with implementations of carry - free addition and subtraction are proposed. The original comparison multiples based implementation of high - radix SRT division is modified to suit radix 10. The binary and decimal implementations of comparison multiples based division are evaluated for delay. Using the method of logical effort, the radix - 4, radix - 16 and decimal floating - point dividers are found to be faster than corresponding circuits reported in the public literature. Note : ¹ SRT division is a type of non - restoring digit recurrence division. / Thesis (Ph.D.)--School of Electrical and Electronic Engineering, 2005.

Interest in adaptive and distributed systems for routing control in networks has led to the development of a new class of algorithms, which is inspired by the shortest path finding behaviours observed in biological ant colonies. This class utilizes ant-like agents, which autonomously traverse the network and collectively construct a distributed routing policy. Agent-based routing algorithms belonging to this class do not require a complete model of the network, and are able to adapt autonomously to network changes in dynamic and unpredictable environments. Previous studies of these algorithms have been carried out exclusively via the use of simulation-based models. In this thesis, we apply analytic modelling techniques to the study of agent-based routing algorithms. Our aim is to broaden the research in this field, as well as to gain a greater theoretical understanding of some fundamental properties of this class of algorithms. / Thesis (Ph.D.)--School of Applied Mathematics, 2002.

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (M. Phil.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

The study of physical activity is important in improving people���s health as it can help people understand the relationship between physical activity and health. Accelerometers, due to its small size, low cost, convenience and its ability to provide objective information about the frequency, intensity, and duration of physical activity, has become the method of choice in measuring physical activity. Machine learning algorithms based on the featurized representation of accelerometer data have become the most widely used approaches in physical activity prediction. To improve the classification accuracy, this thesis first explored the impact of the choice of data (raw vs processed) as well as the choice of features on the performance of various classifiers. The empirical results showed that the machine learning algorithms with strong regularization capabilities always performed better if provided with the most comprehensive feature set extracted from raw accelerometer signal. Based on the hypothesis that for some time series, the most discriminative information could be found at subwindows of various sizes, the Subwindow Ensemble Model (SWEM) was proposed. The SWEM was designed for the accelerometer-based physical activity data, and classified the time series based on the features extracted from subwindows. It was evaluated on six time series datasets. Three of them were accelerometer-based physical activity data, which the SWEM was designed for, and the rest were different types of time series data chosen from other domains. The empirical results indicated a strong advantage of the SWEM over baseline models on the accelerometerbased physical activity data. Further analysis confirmed the hypothesis that the most discriminative features could be extracted from subwindows of different sizes, and they were effectively used by the SWEM. / Graduation date: 2013

Sorting is one of the more computationally intensive tasks a computer performs. One of the most effective ways to speed up the task of sorting is by using parallel algorithms. When implementing a parallel algorithm, the designer has to make several decisions. Among the decisions are the algorithm and the physical implementation of the algorithm. A dedicated hardware solution is often physically quicker than a software solution. In this thesis, we will investigate the optimization of a hardware implementation of max-min sort. I propose an optimization to the data structures used in the algorithm. The new data structure allows quicker sorting by changing the basic workings of the max-min sort. The results are presented by comparing the new data structure with the original data structure. The thesis also discusses the design and performance issues related to implementing the algorithm in hardware. / Graduation date: 1998

Efficient routing of messages is critical to the performance of multicomputers. Many adaptive routing algorithms have been proposed to improve the network efficiency; however, they can make only short-sighted decisions to choose a channel for message routing because of limited information about network condition. The short-sighted decisions may cause unnecessary waits at the next clock cycle if the adaptive routing algorithm chooses a channel which has high probability of message block at the next clock cycle. In this thesis, look-ahead routing scheme is introduced to provide better performance for conventional adaptive routing algorithms. The look-ahead scheme as an adaptive routing algorithm makes longer-sighted decision to avoid possible blocks at the next clock cycle. This thesis also simulates the XY, the West-First, and the Double-Y channel routing algorithms, which are deterministic, partially-adaptive and fully-adaptive, respectively, in a 16 x 16 mesh network. Their performances are compared and analyzed. The simulation includes the examination of look-ahead effect for the West-First and the Double-Y channel routing algorithms. / Graduation date: 1996

Thesis (M.Eng.)--Memorial University of Newfoundland, 2005. / Includes bibliographical references (leaves 105-112).