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ESANN
2003
13 years 6 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
BIB
2008
109views more  BIB 2008»
13 years 5 months ago
Computational intelligence approaches for pattern discovery in biological systems
Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) ...
Gary B. Fogel
ICANN
2005
Springer
13 years 10 months ago
Can Dynamic Neural Filters Produce Pseudo-Random Sequences?
Abstract. Dynamic neural filters (DNFs) are recurrent networks of binary neurons. Under proper conditions of their synaptic matrix they are known to generate exponentially large c...
Yishai M. Elyada, David Horn
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 5 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
AUSAI
2006
Springer
13 years 8 months ago
Intelligent Control of Mobile Agent Based on Fuzzy Neural Network in Intelligent Robotic Space
This paper introduces Fuzzy Neural Network controller to increase the ability of a mobile robot in reacting to the dynamic environments. States of robot and environment, for exampl...
TaeSeok Jin, HongChul Kim, JangMyung Lee