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NECO
2007
150views more  NECO 2007»
15 years 3 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
NN
2007
Springer
162views Neural Networks» more  NN 2007»
15 years 3 months ago
Learning grammatical structure with Echo State Networks
Echo State Networks (ESNs) have been shown to be effective for a number of tasks, including motor control, dynamic time series prediction, and memorizing musical sequences. Howeve...
Matthew H. Tong, Adam D. Bickett, Eric M. Christia...
NN
2007
Springer
15 years 3 months ago
Recurrent neural network modeling of nearshore sandbar behavior
The temporal evolution of nearshore sandbars (alongshore ridges of sand fringing coasts in water depths less than 10 m and of paramount importance for coastal safety) is commonly ...
Leo Pape, B. Gerben Ruessink, Marco A. Wiering, Ia...
NN
2007
Springer
172views Neural Networks» more  NN 2007»
15 years 3 months ago
A computational neuroscience approach to consciousness
Simultaneous recordings from populations of neurons in the inferior temporal visual cortex show that most of the information about which stimulus was shown is available in the num...
Edmund T. Rolls
OSN
2007
132views more  OSN 2007»
15 years 3 months ago
Intermediate-node-initiation (INI): A generalized signaling framework for optical burst-switched networks
In this paper, we discuss different signaling techniques for optical burst-switched networks. We develop a generalized signaling framework for optical burst-switched networks, whi...
Vinod Vokkarane
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