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» The Learning Power of Evolution
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BC
2007
79views more  BC 2007»
14 years 12 months ago
Spike-timing-dependent plasticity for neurons with recurrent connections
The dynamics of the learning equation, which describes the evolution of the synaptic weights, is derived in the situation where the network contains recurrent connections. The deri...
Anthony N. Burkitt, Matthieu Gilson, J. Leo van He...
77
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IADIS
2004
15 years 1 months ago
Software for self-government
Government bureaucracies are both extremely complex and long-lived, constantly evolving to reflect and influence their ever changing cultural and physical environments. Software s...
Thomas B. Senior, Brian Warboys
ESANN
2003
15 years 1 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre
SKG
2006
IEEE
15 years 5 months ago
Mathematics Computing Environment on the Web
With the rapid evolution of web technology and Internet, the mathematical web has emerged as a new research trend, which changes the traditional manner of mathematical scientific ...
Li Liu, Yi Yang, Lian Li
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
15 years 6 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull