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GECCO
2005
Springer
196views Optimization» more  GECCO 2005»
10 years 6 months ago
Breeding swarms: a new approach to recurrent neural network training
This paper shows that a novel hybrid algorithm, Breeding Swarms, performs equal to, or better than, Genetic Algorithms and Particle Swarm Optimizers when training recurrent neural...
Matthew Settles, Paul Nathan, Terence Soule
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
10 years 5 months ago
Stochastic training of a biologically plausible spino-neuromuscular system model
A primary goal of evolutionary robotics is to create systems that are as robust and adaptive as the human body. Moving toward this goal often involves training control systems tha...
Stanley Phillips Gotshall, Terence Soule
IJON
2007
118views more  IJON 2007»
10 years 1 months ago
Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm
To predict the 100 missing values from a time series of 5000 data points, given for the IJCNN 2004 time series prediction competition, recurrent neural networks (RNNs) are trained...
Xindi Cai, Nian Zhang, Ganesh K. Venayagamoorthy, ...
EAAI
2006
123views more  EAAI 2006»
10 years 1 months ago
Imitation learning with spiking neural networks and real-world devices
This article is about a new approach in robotic learning systems. It provides a method to use a real-world device that operates in real-time, controlled through a simulated recurr...
Harald Burgsteiner
TNN
1998
111views more  TNN 1998»
10 years 28 days ago
Modular recurrent neural networks for Mandarin syllable recognition
Abstract—A new modular recurrent neural network (MRNN)based speech-recognition method that can recognize the entire vocabulary of 1280 highly confusable Mandarin syllables is pro...
Sin-Horng Chen, Yuan-Fu Liao
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