Browsing Doctoral Theses by Thesis Supervisor "Kasabov, Nikola"
Now showing items 1-20 of 26
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Adaptive Methods for Spatiotemporal Stream Data Mining
(Auckland University of Technology, 2018)The availability of temporal and spatiotemporal data is increasing, and the use of traditional statistical techniques to deal with such data is insufficient. Novel methods that are capable of adapting to changing patterns ... -
Age Invariant Face Recognition Via Aging Modelling
(Auckland University of Technology, 2017)Aging is a complex problem because at different age points different changes occur in the human face. From childhood to teenage the changes are mostly related to craniofacial growth. At maturity the changes are mostly ... -
An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case
(Auckland University of Technology, 2010)The explosive growth in the volume of data and the growing number of disparate data sources is bringing enormous opportunities and challenges to many research communities. In the biomedical domain, the challenge of knowledge ... -
Computational Modelling of Spatio-Temporal EEG Brain Data with Spiking Neural Networks
(Auckland University of Technology, 2015)The research presented in this thesis is aimed at modelling, classification and understanding of functional changes in brain activity that forewarn of the onset and/or the progression of a neurodegenerative process that ... -
Connectionist methods for data analysis and modelling of human motion in sporting activities
(Auckland University of Technology, 2012)This research concerns automation of qualitative analysis of human motion in sports, using a novel approach related to assessment and diagnostics, which is required to provide a general user with coaching experience in ... -
Development of a new computational model for mapping, learning and mining of 3D spatio-temporal fMRI data
(Auckland University of Technology, 2015)The application of data mining techniques, particularly classification of spatio-temporal 3D functional magnetic resonance images has received growing attention in the literature. Spatio or spatial component as well as ... -
Development of Spiking Neural Network Methods for Spatio-temporal Brain Data Analysis
(Auckland University of Technology, 2019)This thesis proposes methods employing an evolving Spiking Neural Network (SNN) architecture for the analysis of spatio-temporal neuroimaging data. Multivariate Spatio-Temporal Brain Data (STBD) is intrinsically complex ... -
Evolving connectionist systems for adaptive decision support with application in ecological data modelling
(Auckland University of Technology, 2009)Ecological modelling problems have characteristics both featured in other modelling fields and specific ones, hence, methods developed and tested in other research areas may not be suitable for modelling ecological problems ... -
Evolving probabilistic spiking neural networks for modelling and pattern recognition of spatio-temporal data on the case study of Electroencephalography (EEG) brain data
(Auckland University of Technology, 2012)The use of Electroencephalography (EEG) in Brain Computer Interface (BCI) domain presents a challenging problem due to presence of spatial and temporal aspects inherent in the EEG data. Many studies either transform the ... -
Evolving spiking neural networks for adaptive audiovisual pattern recognition
(Auckland University of Technology, 2008)This dissertation presents new modular and integrative information methods and systems inspired by the way the brain performs information processing, in particular, pattern recognition. The proposed artificial systems use ... -
Evolving Spiking Neural Networks for Spatio- and Spectro- Temporal Data Analysis: Models, Implementations, Applications
(Auckland University of Technology, 2015)Arguably the most significant challenge in modern machine learning regards how we address the complexities of Spatio- and Spectro-Temporal Data (SSTD); i.e., data with some spatial, spectral, and temporal component. ... -
Heterogeneous probabilistic models for optimisation and modelling of evolving spiking neural networks
(Auckland University of Technology, 2010)This thesis proposes a novel feature selection and classification method employing evolving spiking neural networks (eSNN) and evolutionary algorithms (EA). The method is named the Quantum-inspired Spiking Neural Network ... -
Integrated multi-model framework for adaptive multiple time-series analysis and modelling
(Auckland University of Technology, 2011)The topic of time-series prediction has been very well researched in studies of dynamic systems. However, most studies in the field have focused more on predicting movement of a single time-series only, whilst prediction ... -
Integrative approaches to modelling and knowledge discovery of molecular interactions in bioinformatics
(Auckland University of Technology, 2008)The core focus of this research lies in developing and using intelligent methods to solve biological problems and integrating the knowledge for understanding the complex gene regulatory phenomenon. We have developed an ... -
Local and personalised models for prediction, classification and knowledge discovery on real world data modelling problems
(Auckland University of Technology, 2009)This thesis presents several novel methods to address some of the real world data modelling issues through the use of local and individualised modelling approaches. A set of real world data modelling issues such as modelling ... -
Mnemotechne of design — ontology and design research theories
(Auckland University of Technology, 2010)This thesis commences with the premise that while design practices may be said to have a very long, perhaps ancient, history, ‘Design’ as a discipline is of more recent origin, while ‘Design Research’ as a disciplinary ... -
Modelling of Spatiotemporal EEG and ERP Brain Data for Dynamic Pattern Recognition and Brain State Prediction using Spiking Neural Networks: Methods and Applications in Psychology
(Auckland University of Technology, 2019)This thesis aimed to improve modelling and understanding of spatiotemporal brain data underpinning human behaviour with the use of a brain-inspired artificial intelligence technique: spiking neural networks (SNN). These ... -
Neuromorphic computational models for machine learning and pattern recognition from multi-modal time-series data
(Auckland University of Technology, 2018)The fields of neuroscience and artificial intelligence have a long and entwined history. In recent times, however, communication and collaboration between the two fields has become a rarity as they have evolved. Written ... -
Novel Integrated Methods of Evolving Spiking Neural Network and Particle Swarm Optimisation
(Auckland University of Technology, 2012)This thesis proposes and presents several methods for classification problems. Spatial and spatiotemporal classification problems have been considered in this study. A novel integration between Evolving Spiking Neural ... -
On-line fast kernel based methods for classification over stream data (with case studies for cyber-security)
(Auckland University of Technology, 2012)This thesis proposes and presents several novel methods to address some of the real world stream data modelling issues through the use of global and local modelling approaches. A set of real world stream data modelling ...