Mixture Model Clustering For Very Large Data Sets.,
2010
Universiti Malaya
Mixture Model Clustering For Very Large Data Sets., Leong Siow Hoo
Student Works (2010-2019)
This thesis develops mixture model clustering algorithms scalable to data sets that do not fit into the computer memory buffer. Two algorithms, FlexClust and FlexClustMix, are proposed for clustering very large continuous and mixed data sets respectively. The basic framework of the algorithms is to scale down data incrementally using data compression, and incorporates the later compressed data into the current model with the ability to recover new clusters that have been missed out in the earlier compressed data. It consists of three modules: 1) incremental compression, 2) detecting change in cluster structure, and 3) update of current model. In …
Fractional Anisotropic Diffusion For Noise Reduction In Magnetic Resonance Images,
2010
Technological University Dublin
Fractional Anisotropic Diffusion For Noise Reduction In Magnetic Resonance Images, Jonathan Blackledge, Matthew Blackledge
Articles
We extend the method of anisotropic diffusion for noise reduction in digital images to the case when the diffusion processes are non-Gaussian and Levy distributed. This yields a fractional diffusion equation characterised by the Levy index. A solution to this equation is considered and a numerical algorithm developed. The algorithm is then applied as a case study to the problem of reducing noise in magnetic resonance imaging. The focus of this study is on diffusion weighted images which have low signal-to-noise ratios.
Economic Risk Assessment Using The Fractal Market Hypothesis,
2010
Technological University Dublin
Economic Risk Assessment Using The Fractal Market Hypothesis, Jonathan Blackledge, Marek Rebow
Conference papers
This paper considers the Fractal Market Hypothesi (FMH) for assessing the risk(s) in developing a financial portfolio based on data that is available through the Internet from an increasing number of sources. Most financial risk management systems are still based on the Efficient Market Hypothesis which often fails due to the inaccuracies of the statistical models that underpin the hypothesis, in particular, that financial data are based on stationary Gaussian processes. The FMH considered in this paper assumes that financial data are non-stationary and statistically self-affine so that a risk analysis can, in principal, be applied at any time scale …
Encryption Using Deterministic Chaos,
2010
Technological University Dublin
Encryption Using Deterministic Chaos, Jonathan Blackledge, Nikolai Ptitsyn
Articles
The concepts of randomness, unpredictability, complexity and entropy form the basis of modern cryptography and a cryptosystem can be interpreted as the design of a key-dependent bijective transformation that is unpredictable to an observer for a given computational resource. For any cryptosystem, including a Pseudo-Random Number Generator (PRNG), encryption algorithm or a key exchange scheme, for example, a cryptanalyst has access to the time series of a dynamic system and knows the PRNG function (the algorithm that is assumed to be based on some iterative process) which is taken to be in the public domain by virtue of the Kerchhoff-Shannon …
