Browsing School of Engineering, Computer & Mathematical Sciences by Author "Kasabov, N"
Now showing items 1-20 of 23
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A novel evolving clustering algorithm with polynomial regression for chaotic time-series prediction
Widiputra, H; Kho, H; Lukas; Pears, R; Kasabov, N (Springer Berlin Heidelberg, 2009)Time-series prediction has been a very well researched topic in recent studies. Some popular approaches to this problem are the traditional statistical methods e.g. multiple linear regression and moving average, and neural ... -
Bioengineering silicon quantum dot theranostics using a network analysis of metabolomic and proteomic data in cardiac ischemia
Erogbogbo, F; May, J; Swihart, M; Prasad, P; Smart, K; Jack, S; Korcyk, D; Webster, M; Stewart, R; Zeng, I; Jullig, M; Bakeev, K; Jamieson, M; Kasabov, N; Gopalan, B; Liang, L; Hu, R; Schliebs, S; Villas-Boas, S; Gladding, P (Ivyspring International Publisher, 2013)Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be ... -
Brain, gene, and quantum inspired computational intelligence
Kasabov, N (Springer-Verlag, 2014)This chapter discusses opportunities and challenges for the creation of methods of computational intelligence (CI) and more specifically – artificial neural networks (ANN), inspired by principles at different levels of ... -
Classification and Segmentation of fMRI Spatio-temporal Brain Data With a Neucube Evolving Spiking Neural Network Model
Doborjeh, MG; Capecci, E; Kasabov, N (Institute of Electrical and Electronics Engineers Inc., 2014)The proposed feasibility analysis introduces a new methodology for modelling and understanding functional Magnetic Resonance Image (fMRI) data recorded during human cognitive activity. This constitutes a type of Spatio-Temporal ... -
Computational modeling with spiking neural networks
Schliebs, S; Kasabov, N (Springer-Verlag Berlin, 2014)This chapter reviews recent developments in the area of spiking neural networks (SNN) and summarizes the main contributions to this research field. We give background information about the functioning of biological neurons, ... -
Contemporary developments in neural networks: spiking neural networks for adaptive spatio-/spectro temporal pattern recognition
Kasabov, N (International Conference on Artificial Neural Networks (ICANN), 2013)No abstract. -
Dynamic Interaction Networks in modelling and predicting the behaviour of multiple interactive stock markets
Widiputra, H; Pears, R; Serguieva, A; Kasabov, N (John Wiley & Sons, 2009)The behaviour of multiple stock markets can be described within the framework of complex dynamic systems. A representative technique of the framework is the dynamic interaction network (DIN), recently developed in the ... -
EEG signal processing for brain-computer interfaces
Georgieva, P; Silva, F; Milanova, M; Kasabov, N (Springer-Verlag, 2014)This chapter is focused on recent advances in electroencephalogram (EEG) signal processing for brain computer interface (BCI) design. A general overview of BCI technologies is first presented, and then the protocol for ... -
Evolving computational intelligence: methods, systems, applications
Kasabov, N (International Conference on Intelligent Computing (ICIC), 2013)The talk presents an overview of current methods of computational intelligence (CI) called evolving CI (eCI) and how they can be used in to create adaptive, computational intelligence (CI) systems across areas of applications. ... -
Evolving integrated multi-model framework for on line multiple time series prediction
Pears, R; Widiputra, H; Kasabov, N (Springer, 2013)Time series prediction has been extensively researched in both the statistical and computational intelligence literature with robust methods being developed that can be applied across any given application domain. A much ... -
Evolving spiking neural network - a survey
Schliebs, S; Kasabov, N (Springer, 2013)This paper provides a comprehensive literature survey on the evolving Spiking Neural Network (eSNN) architecture since its introduction in 2006 as a further extension of the ECoS paradigm introduced by Kasabov in 1998. We ... -
Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke
Kasabov, N; Feigin, V; Hou, Z-G; Chen, Y; Liang, L; Krishnamurthi, R; Othman, M; Parmar, P (Elsevier, 2014)The paper presents a novel method and system for personalised (individualised) modelling of spatio/spectro-temporal data (SSTD) and prediction of events. A novel evolving spiking neural network reservoir system (eSNNr) is ... -
Evolving, probabilistic spiking neural networks and neurogenetic systems for spatio- and spectro-temporal data modelling and pattern recognition
Kasabov, N (The International Neural Network Society (INNS), 2012)Spatio- and spectro-temporal data (SSTD) are the most common types of data collected in many domain areas, including engineering, bioinformatics, neuroinformatics, ecology, environment, medicine, economics, etc. However, ... -
Information methods for predicting risk and outcome of stroke
Liang, L; Krishnamurthi, R; Kasabov, N; Feigin, V (Springer Verlag, 2014)Stroke is a major cause of disability and mortality in most economically developed countries. It is the second leading cause of death worldwide (after cancer and heart disease) [55.1, 2] and a major cause of disability in ... -
Mapping, learning and mining of spatiotemporal brain data with 3D evolving spiking neurogenetic models
Kasabov, N (The Neuromorphic Cognitive Systems group, at the Institute of Neuroinformatics, University of Zurich and ETH Zurich, 2012)Spatio- and spectro-temporal data are the most common data in many domain areas, including bioinformatics and neuroinformatics. Still there are no sufficient methods to model such data and to discover complex spatio-temporal ... -
Neurocomputation as brain inspired informatics: methods, systems, applications
Kasabov, N (Panhellenic Conference on Informatics, 2013)Neuromputation is concerned with methods, systems and applications inspired by the principles of information processing in the brain. The talk presents a brief overview of methods of neurocomputation, including: traditional ... -
Neurocomputing for spatio-/spectro temporal pattern recognition and early event prediction: methods, systems, applications
Kasabov, N (Engineering Applications of Neural Networks (EANN), 2013)The talk presents a brief overview of contemporary methods for neurocomputation, including: evolving connections systems (ECOS) and evolving neuro-fuzzy systems [1]; evolving spiking neural networks (eSNN) [2-5]; evolutionary ... -
Ontologies and machine learning systems
Tegginmath, S; Pears, R; Kasabov, N (Springer, 2014)In this chapter we review the uses of ontologies within bioinformatics and neuroinformatics and the various attempts to combine machine learning (ML) and ontologies, and the uses of data mining ontologies. This is a diverse ... -
Personalised information modelling technologies for personalised medicine
Hu, Y; Kasabov, N; Liang, W (Springer, 2014)Personalised modelling offers a new and effective approach for the study in pattern recognition and knowledge discovery, especially for biomedical applications. The created models are more useful and informative for analysing ... -
Personalised modelling for multiple time-series data prediction
Widiputra, H; Pears, R; Kasabov, N (Springer-Verlag, 2008)The behaviour of multiple stock markets can be described within the framework of complex dynamic systems (CDS). Using a global model with the Kalman Filter we are able to extract the dynamic interaction network (DIN) of ...