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NECO
2006
76views more  NECO 2006»
13 years 7 months ago
Spontaneous Dynamics of Asymmetric Random Recurrent Spiking Neural Networks
We study in this paper the effect of an unique initial stimulation on random recurrent networks of leaky integrate and fire neurons. Indeed given a stochastic connectivity this so...
Hédi Soula, Guillaume Beslon, Olivier Mazet
SOFSEM
2004
Springer
14 years 22 days ago
Approaches Based on Markovian Architectural Bias in Recurrent Neural Networks
Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...
Matej Makula, Michal Cernanský, Lubica Benu...
TNN
2008
138views more  TNN 2008»
13 years 7 months ago
A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Zhenzhen Liu, Itamar Elhanany
NC
1998
140views Neural Networks» more  NC 1998»
13 years 8 months ago
Recurrent Neural Networks with Iterated Function Systems Dynamics
We suggest a recurrent neural network (RNN) model with a recurrent part corresponding to iterative function systems (IFS) introduced by Barnsley 1] as a fractal image compression ...
Peter Tiño, Georg Dorffner
CIBCB
2005
IEEE
14 years 1 months ago
Artificial Neural Network Analysis of DNA Microarray-based Prostate Cancer Recurrence
— DNA microarray-based gene expression profiles have been established for a variety of adult cancers. This paper addresses application of an artificial neural network (ANN) wit...
Leif E. Peterson, Mustafa Ozen, Halime Erdem, Andr...