Now showing items 1-10 of 44
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 ...
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 ...
Transductive modeling with GA parameter optimization
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 ...
DENFIS: dynamic evolving neural-fuzzy inference system and its application for time series prediction
This paper introduces a new type of fuzzy inference systems, denoted as dynamic evolving neural-fuzzy inference system (DENFIS), for adaptive online and offline learning, and their application for dynamic time series ...
Quantum-inspired particle swarm optimization for feature selection and parameter optimization in evolving spiking neural networks for classification tasks
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 ...
Mobile robot navigation - some issues in controller design and implementation
(IEEE Instrumentation and Measurement, Malaysia (IM), 2009)
Neuro-, genetic-, and quantum inspired evolving intelligent systems
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 ...
TWNFC - Transductive neural-fuzzy classifier with weighted data normalization and its application in medicine
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 ...
Computational neurogenetic modeling: a methodology to study gene interactions underlying neural oscillations
We present new results from Computational Neurogenetic Modeling to aid discoveries of complex gene interactions underlying oscillations in neural systems. Interactions of genes in neurons affect the dynamics of the whole ...
Evolutionary Computation for Dynamic Parameter Optimisation of Evolving Connectionist Systems for On-line Prediction of Time Series with Changing Dynamics
The paper describes a method of using evolutionary computation technique for parameter optimisation of evolving connectionist systems (ECOS) that operate in an online, life-long learning mode. ECOS evolve their structure ...