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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 ...
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 weight dilution
(2001)
The consequences of diluting the weights of the standard Hopfield architecture associative memory model, trained using perceptron like learning rules, is examined. A proportion of the weights of the network are removed; ...
Towards Computational Neural Systems through Developmental Evolution
(2001)
The capability of creating artificial neural networks with biologically-plausible characteristics, is becoming ever more attainable through the greater understanding of biological neural systems and the constant increases ...
Omni-directional motion: pedestrian shape classification using neural networks and active contour models
(2001)
This paper describes a hybrid vision system which, following initial user interaction, can detect and track objects in the visual field, and classify them as human and non-human. The system incorporates an active contour ...