Finding information hidden in data is as theoretically difficult as it is practically important.
With the objective of discovering unknown patterns from data, the methodologies of data …

This valuable text addresses different pattern recognition (PR) tasks in a unified framework
with both theoretical and experimental results. Tasks covered include data condensation …

A methodology is described for evolving a Rough-fuzzy multi layer perceptron with modular
concept using a genetic algorithm to obtain a structured network suitable for both …

This article describes a way of integrating rough set theory with a fuzzy MLP using a modular
evolutionary algorithm, for classification and rule generation in soft computing paradigm …

An Indexed Bibliography of Genetic Algorithms and Neural Networks Page 1 An Indexed
Bibliography of Genetic Algorithms and Neural Networks compiled by Jarmo T. Alander …

This paper describes a hierarchical evolutionary technique developed to design and train
feedforward neural networks with different activation functions on their hidden-layer neurons …

Evolving connectionist systems: Characterisation, simplification, formalisation, explanation
and optimisation - University of Otago Logo image Menu Outputs Thesis Deposit Guide FAQs …

An Indexed Bibliography of Genetic Algorithms in Biosciences Page 1 An Indexed Bibliography
of Genetic Algorithms in Biosciences compiled by Jarmo T. Alander Department of Information …

This work describes an evolutionary system to control the growth of a constructive neural
network for autonomous navigation. A classifier system generates Takagi-Sugeno fuzzy …

We propose a pure topological recurrent networks controller, which has random binary
connections in hidden layer, and all hidden neurons are activated by sinusoidal functions. A …