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Comparative performances of stochastic competitive evolutionary neural tree (SCENT) with neural classifiers
(2001)
A stochastic competitive evolutionary neural tree (SCENT) is described and evaluated against the best neural classifiers with equivalent functionality, using a collection of data sets chosen to provide a variety of clustering ...
The Analysis of the addition of Stochasticity to a Neural Tree Classifier
(2001)
This paper describes various mechanisms for adding stochasticity to a dynamic hierarchical neural clusterer. Such a network grows a tree-structured neural classifier dynamically in response to the unlabelled data with which ...
High performance associative memory models and sign constraints
(2001)
The consequences of imposing a sign constraint on the standard Hopfield architecture associative memory model, trained using perceptron like learning rules, is examined. Such learning rules have been shown to have capacity ...
A comparative analysis of high performance associative memory models.
(2000)
Three variants of the Hopfield network are examined, each of which is trained using a different iterative approximation of the pseudo-inverse rule. All three variants are known to have significantly higher memory capacity ...
Input window size and neural network predictors
(Institute of Electrical and Electronics Engineers (IEEE), 2000)
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 briefly ...
The Architecture and Performance of a Stochastic Competitive Evolutionary Neural Tree Network
(2000)
A new dynamic tree structured network - the Stochastic Competitive Evolutionary Neural Tree (SCENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage ...
High performance associative memory models and symmetric connections
(2000)
Two existing high capacity training rules for the standard Hopfield architecture associative memory are examined. Both rules, based on the perceptron learning rule produce asymmetric weight matrices, for which the simple ...
Analysis of human motion using snakes and neural networks
(2000)
A novel technique is described for analysing human movement in outdoor scenes. Following initial detection of the humans using active contour models, the contours are then re-represented as normalised axis crossover vectors. ...