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.
['Shawn E. Taylor', 'Michael L. Bernard', 'Stephen J. Verzi', 'James Dan Morrow', 'Craig M. Vineyard', 'Michael J. Healy', 'Thomas P. Caudell']
Temporal semantics: An Adaptive Resonance Theory approach