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GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
13 years 10 months ago
A Descriptive Encoding Language for Evolving Modular Neural Networks
Evolutionary algorithms are a promising approach for the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to repres...
Jae-Yoon Jung, James A. Reggia
ICANN
2009
Springer
13 years 9 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
AIA
2006
13 years 6 months ago
Recurrent and Concurrent Neural Networks for Objects Recognition
A system based on a neural network framework is considered. We used two neural networks, an Elman network [1][2] and a Kohonen (concurrent) network [3], for a categorization task....
Federico Cecconi, Marco Campenní
AGI
2011
12 years 8 months ago
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
Human intelligence consists largely of the ability to recognize and exploit structural systematicity in the world, relating our senses simultaneously to each other and to our cogni...
Derek Monner, James A. Reggia
JUCS
2007
107views more  JUCS 2007»
13 years 5 months ago
Genetic Algorithm Based Recurrent Fuzzy Neural Network Modeling of Chemical Processes
: A genetic algorithm (GA) based recurrent fuzzy neural network modeling method for dynamic nonlinear chemical process is presented. The dynamic recurrent fuzzy neural network (RFN...
Jili Tao, Ning Wang, Xuejun Wang