Browsing KEDRI - the Knowledge Engineering and Discovery Research Institute by Title
Now showing items 34-53 of 54
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Mapping temporal variables into the NeuCube for improved pattern recognition, predictive modeling, and understanding of stream data
(IEEE, 2016)This paper proposes a new method for an optimized mapping of temporal variables, describing a temporal stream data, into the recently proposed NeuCube spiking neural network (SNN) architecture. This optimized mapping extends ... -
Method for training a spiking neuron to associate input-output spike trains
(AUT University, 2011)We propose a novel supervised learning rule allowing the training of a precise input-output behavior to a spiking neuron. A single neuron can be trained to associate (map) different output spike trains to different multiple ... -
Mobile robot navigation - some issues in controller design and implementation
(IEEE Instrumentation and Measurement, Malaysia (IM), 2009) -
Modelling peri-perceptual brain processes in a deep learning spiking neural network architecture
(Macmillan Publishers Limited, 2018)Familiarity of marketing stimuli may affect consumer behaviour at a peri-perceptual processing level. The current study introduces a method for deep learning of electroencephalogram (EEG) data using a spiking neural network ... -
Modelling the effect of genes on the dynamics of probabilistic spiking neural networks for computational neurogenetic modelling
(AUT University, 2011)Computational neuro-genetic models (CNGM) combine two dynamic models – a gene regulatory network (GRN) model at a lower level, and a spiking neural network (SNN) model at a higher level to model the dynamic interaction ... -
Network-based method for inferring cancer progression at the pathway level from cross-sectional mutation data
(IEEE, 2016)Large-scale cancer genomics projects are providing a wealth of somatic mutation data from a large number of cancer patients. However, it is difficult to obtain several samples with a temporal order from one patient in ... -
Neural Systems for solving the inverse problem of recovering the Primary Signal Waveform in potential transformers
(IEEE, 2003)The inverse problem of recovering the potential transformer primary signal waveform using secondary signal waveform and information about the secondary load is solved here via two inverse neural network models. The first ... -
Neuro-, genetic-, and quantum inspired evolving intelligent systems
(IEEE, 2006)This paper discusses opportunities and challenges for the creation of evolving artificial neural network (ANN) and more general - computational intelligence (CI) models inspired by principles at different levels of information ... -
New Algorithms for Encoding, Learning and Classification of fMRI Data in a Dpiking Neural Network Architecture: A Case on Modelling and Understanding of Dynamic Cognitive
(IEEE, 2016)The paper argues that, the third generation of neural networks – the spiking neural networks (SNN), can be used to model dynamic, spatio-temporal, cognitive brain processes measured as functional magnetic resonance imaging ... -
NFI: a neuro-fuzzy inference method for transductive reasoning
(IEEE, 2005)This paper introduces a novel neural fuzzy inference method - NFI for transductive reasoning systems. NFI develops further some ideas from DENFIS - dynamic neuro-fuzzy inference systems for both online and offline time ... -
On-line evolving fuzzy clustering
(IEEE, 2007)In this paper, a novel on-line evolving fuzzy clustering method that extends the evolving clustering method (ECM) of Kasabov and Song (2002) is presented, called EFCM. Since it is an on-line algorithm, the fuzzy membership ... -
Optimisation and modelling of spiking neural networks - Enhancing neural information processing systems through the power of evolution
(LAP LAMBERT Academic Publishing, 2010)Motivated by the desire to better understand the truly remarkable information processing capabilities of the brain, numerous biologically plausible computational models have been explored in the recent decades. Already ... -
Personalised Modelling on Integrated Clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network System
(IEEE, 2016)This paper introduces a novel personalised modelling framework and system for analysing Spatio-Temporal Brain Data (STBD) along with person clinical static data. For every individual, based on selected subset of similar ... -
Quantum-inspired feature and parameter optimization of evolving spiking neural networks with a case study from ecological modelling
(IEEE, 2009)The paper introduces a framework and implementation of an integrated connectionist system, where the features and the parameters of an evolving spiking neural network are optimised together using a quantum representation ... -
Quantum-inspired particle swarm optimization for feature selection and parameter optimization in evolving spiking neural networks for classification tasks
(InTech, 2011)Introduction: Particle Swarm Optimization (PSO) was introduced in 1995 by Russell Eberhart and James Kennedy (Eberhart & Kennedy, 1995). PSO is a biologically-inspired technique based around the study of collective behaviour ... -
Robotics for engineering education
(Robocup - Singapore, 2010)Most products are the integration of modules from different engineering areas – mechanical, electrical and electronics, computing etc. Engineering graduates are expected to design, manufacture and control those ... -
SPAN: Spike Pattern Association Neuron for learning spatio-temporal sequences
(World Scientific Publishing Company, 2012)Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for ... -
Transductive modeling with GA parameter optimization
(IEEE, 2005)Introduction - While inductive modeling is used to develop a model (function) from data of the whole problem space and then to recall it on new data, transductive modeling is concerned with the creation of single model for ... -
Transductive Support Vector Machines and Applications in Bioinformatics for Promoter Recognition
(IEEE, 2004)This paper introduces a novel transductive support vector machine (TSVM) model and compares it with the traditional inductive SVM on a key problem in bioinformatics - promoter recognition. While inductive reasoning is ... -
TWNFC - Transductive neural-fuzzy classifier with weighted data normalization and its application in medicine
(IEEE, 2005)This paper introduces a novel fuzzy model - transductive neural-fuzzy classifier with weighted data normalization (TWNFC), While inductive approaches are concerned with the development of a model to approximate data in the ...