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ACSC
2008
IEEE
13 years 9 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish
BC
2002
193views more  BC 2002»
13 years 7 months ago
Resonant spatiotemporal learning in large random recurrent networks
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Emmanuel Daucé, Mathias Quoy, Bernard Doyon
NIPS
2007
13 years 8 months ago
An in-silico Neural Model of Dynamic Routing through Neuronal Coherence
We describe a neurobiologically plausible model to implement dynamic routing using the concept of neuronal communication through neuronal coherence. The model has a three-tier arc...
Devarajan Sridharan, Brian Percival, John V. Arthu...
IJON
1998
95views more  IJON 1998»
13 years 7 months ago
Self-organization and segmentation in a laterally connected orientation map of spiking neurons
The RF-SLISSOM model integrates two separate lines of research on computational modeling of the visual cortex. Laterally connected self-organizing maps have been used to model how...
Yoonsuck Choe, Risto Miikkulainen
ITS
2004
Springer
155views Multimedia» more  ITS 2004»
14 years 24 days ago
Modeling the Development of Problem Solving Skills in Chemistry with a Web-Based Tutor
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...
Ron Stevens, Amy Soller, Melanie Cooper, Marcia Sp...