Proceedings ArticleDOI
Distributed Optimization With The ALOPEX Algorithms
Ivan Marsic,Evangelia Micheli-Tzanakou +1 more
- pp 1415-1416
TLDR
A method of distributed optimization using the ALOPEX algorithm and a paradigm of temperature spreading and applications to the problem of pattern recognition are presented.Abstract:
A method of distributed optimization using the ALOPEX algorithm and a paradigm of temperature spreading is described. It shows several desirable properties: the number of iterations is significantly smaller than with the global optimization and independent on the data set size; a stopping condition is introduced; the biological plausibility for neural network implementations is also maintained. In particular, applications to the problem of pattern recognition are presented.read more
Citations
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Journal ArticleDOI
Detection of multiple sclerosis with visual evoked potentials - an unsupervised computational intelligence system
T.J. Dasey,E. Micheli-Tzanakou +1 more
TL;DR: This analysis hints at the usefulness of previously unused portions of the VEP in detecting MS, and indicates a possible use of the system as a training aide.
Journal ArticleDOI
When a feature detector becomes a feature generator
TL;DR: The neural network approach is reviewed in the context of studies in the animal and human visual systems and an attempt is made to explain perception, memory and learning as a feedback loop similar to the one used in the ALOPEX optimization concept.
Proceedings ArticleDOI
A Knowledge Based Neural Network Classifier For Visual Evoked Potentials
TL;DR: A knowledge based Neural Networks classifier for Visual Evoked Potentials is designed and implemented, a hybrid of a knowledge based classifier using different Neural Network techniques.
References
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Journal ArticleDOI
Computational vision and regularization theory
TL;DR: Descriptions of physical properties of visible surfaces, such as their distance and the presence of edges, must be recovered from the primary image data and algorithms and parallel analog circuits that can solve ‘ill-posed problems’ and which are suggestive of neural equivalents in the brain are proposed.
Book
Computational vision and regularization theory
TL;DR: A recent development in this field sees early vision as a set of ill-posed problems, which can be solved by the use of regularization methods as discussed by the authors, which are suggestive of neural equivalents in the brain.
Journal ArticleDOI
An analogue approach to the travelling salesman problem using an elastic net method
TL;DR: This work describes how a parallel analogue algorithm, derived from a formal model for the establishment of topographically ordered projections in the brain, can be applied to the travelling salesman problem, and produces shorter tour lengths than another recent parallel analogue algorithms.