Title :
Temporal semantics: An Adaptive Resonance Theory approach
Author :
Taylor, S.E. ; Bernard, M.L. ; Verzi, S.J. ; Morrow, J.D. ; Vineyard, C.M. ; Healy, M.J. ; Caudell, T.P.
Author_Institution :
Sandia Nat. Labs., Albuquerque, NM, USA
Abstract :
Encoding sensor observations across time is a critical component in the ability to model cognitive processes. All biological cognitive systems receive sensory stimuli as continuous streams of observed data over time. Therefore, the perceptual grounding of all biological cognitive processing is in temporal semantic encodings, where the particular grounding semantics are sensor modalities. We introduce a technique that encodes temporal semantic data as temporally integrated patterns stored in adaptive resonance theory (ART) modules.
Keywords :
ART neural nets; adaptive codes; cognitive systems; temporal reasoning; ART; adaptive resonance theory approach; artificial neural architecture; biological cognitive system; sensor observation encoding; temporal semantics; temporally integrated pattern; Biological information theory; Biological neural networks; Biological system modeling; Biosensors; Encoding; Grounding; Neural networks; Resonance; Subspace constraints; Unsupervised learning;
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2009.5178925
