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IWSOS
2011
Springer
14 years 10 months ago
Evolving Self-organizing Cellular Automata Based on Neural Network Genotypes
Abstract This paper depicts and evaluates an evolutionary design process for generating a complex self-organizing multicellular system based on Cellular Automata (CA). We extend th...
Wilfried Elmenreich, István Fehérv&a...
180
Voted
IJCNN
2006
IEEE
16 years 1 months ago
Training Reformulated Product Units in Hybrid Neural Networks
— Higher order networks allow modelling of correlates and geometrically invariant properties. Current techniques for their development either require domain knowledge, or are con...
Philip T. Elliott, Diven Topiwala, Will N. Browne
183
Voted
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
15 years 12 months ago
Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks
In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients were analyzed using a hybrid neural networks training algorithm. This algorithm combines genetic algorithm...
Adam V. Adamopoulos, Efstratios F. Georgopoulos, S...
161
Voted
WCE
2007
15 years 8 months ago
E-learning System Based on Neural Networks
—Although the current E-Learning systems have many merits, many of them only treat advanced information technology as simple communication tools, and release some learning conten...
Linfeng Zhang, Fei Yu, Yue Shen, Guiping Liao, Ken...
195
Voted
BIOSYSTEMS
2007
82views more  BIOSYSTEMS 2007»
15 years 7 months ago
Homeostatic plasticity improves signal propagation in continuous-time recurrent neural networks
Continuous-time recurrent neural networks (CTRNNs) are potentially an excellent substrate for the generation of adaptive behaviour in artificial autonomous agents. However, node ...
Hywel T. P. Williams, Jason Noble