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Now showing items 171-180 of 185
Time series prediction and neural networks
(1999)
Neural Network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results from dynamic systems theory are introduced, ...
Applications of neural networks to telecommunications systems
(ELITE Foundation, 1999)
This paper gives an overview of a project involving the application of neural networks to Telecommunications Systems. Five application areas are discussed, including cloned software identification and the detection of ...
An investigation into Karmilov-Smith's RR model : the effects of structured tuition
(1999)
Karmiloff-Smith's model of representational redescription describes development proceeding from implicit to explicit knowledge. During part of this process, knowledge is said to be resistant to external influences. However, ...
Hierarchical Classification with a Competitive Evolutionary Neural Tree
(1999)
A new, dynamic, tree structured network, the Competitive Evolutionary Neural Tree (CENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage that the CENT ...
A Connectionist account of Spanish determiner production
(Springer Nature, 1998)
A Connectionist Network that models the production of simple phonologically coded Spanish Noun Phrases is described. The training data uses type/token frequencies taken directly from a Spanish child's linguistic environment. ...
Analysing Hierarchical Data Using a Stochastic Evolutionary Neural Tree
(1998)
SCENT is simple competitive neural network model that evolves a tree structured set of nodes in response to being presented with an unlabelled data set. The resulting set of weight vectors and their relationship can be ...
A neural network model of visual object recognition impairment after brain damage
(1998)
Dysfunction of the visual object recognition system in humans is briefly discussed and a basic connectionist model of visual object recognition is introduced. Experimentation in which two variants of this model are lesioned ...
An investigation into the performance and representation of a stochastic evolutionary neural tree
(Springer Nature, 1997)
The Stochastic Competitive Evolutionary Neural Tree (SCENT) is a new unsupervised neural net that dynamically evolves a representational structure in response to its training data. Uniquely SCENT requires no initial parameter ...
Traffic trends analysis using neural networks
(1997)
An application of time series prediction, to traffic forecasting in ATM networks, using neural nets is described. One key issue, the number of data points needed to be included in the input representation to the net is ...