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» Analog Hardware Model for Morphological Neural Networks
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IJCNN
2006
IEEE
14 years 1 months ago
Modeling Cortical Maps with Feed-Backs
Abstract— High-level specification of how the brain represents and categorizes the causes of its sensory input allows to link “what is to be done” (perceptual task) with “...
Thierry Viéville, Pierre Kornprobst
IGPL
2010
97views more  IGPL 2010»
13 years 6 months ago
A symbolic/subsymbolic interface protocol for cognitive modeling
Researchers studying complex cognition have grown increasingly interested in mapping symbolic cognitive architectures onto subsymbolic brain models. Such a mapping seems essential...
Patrick Simen, Thad A. Polk
VISUALIZATION
2005
IEEE
14 years 1 months ago
Opening the Black Box - Data Driven Visualization of Neural Network
Arti cial neural networks are computer software or hardware models inspired by the structure and behavior of neurons in the human nervous system. As a powerful learning tool, incr...
Fan-Yin Tzeng, Kwan-Liu Ma
FSS
2008
147views more  FSS 2008»
13 years 7 months ago
A general framework for fuzzy morphological associative memories
Fuzzy associative memories (FAMs) can be used as a powerful tool for implementing fuzzy rule-based systems. The insight that FAMs are closely related to mathematical morphology (M...
Marcos Eduardo Valle, Peter Sussner
CISS
2008
IEEE
14 years 2 months ago
Reconstruction of compressively sensed images via neurally plausible local competitive algorithms
Abstract—We develop neurally plausible local competitive algorithms (LCAs) for reconstructing compressively sensed images. Reconstruction requires solving a sparse approximation ...
Robert L. Ortman, Christopher J. Rozell, Don H. Jo...