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FLAIRS
2004
13 years 6 months ago
Spatiotemporal Novelty Detection Using Resonance Networks
We present a single-layer recurrent neural network that implements novelty detection for spatiotemporal patterns. The architecture is based on the structure of region CA3 in the h...
Benjamin A. Rowland, Anthony S. Maida
BC
2002
193views more  BC 2002»
13 years 5 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
ICNSC
2007
IEEE
13 years 11 months ago
Combined Support Vector Novelty Detection for Multi-channel Combustion Data
— Multi-channel combustion data, consisting of gas pressure and two combustion chamber luminosity measurements, are investigated in the prediction of combustion instability. Wave...
Lei A. Clifton, Hujun Yin, David A. Clifton, Yang ...
ICANN
1997
Springer
13 years 9 months ago
A Novelty Detector Using a Network of Integrate and Fire Neurons
Information in the nervous system has often been considered as being represented by simultaneous discharge of a large set of neurons. We propose a learning mechanism for neural inf...
Tuong Vinh Ho, Jean Rouat
IJCNN
2000
IEEE
13 years 9 months ago
Neural Networks for Novelty Detection in Airframe Strain Data
The structural health of airframes is often monitored by analysis of the frequency of occurrence matrix (FOOM) produced after each flight. Each cell in the matrix records a stres...
Simon J. Hickinbotham, James Austin