Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/42879
Título: Habituation based on spectrogram analysis
Autores/as: Lorenzo, Javier 
Hernández, Mario 
Clasificación UNESCO: 120304 Inteligencia artificial
Fecha de publicación: 2002
Publicación seriada: Lecture Notes in Computer Science 
Conferencia: 8th Ibero-American Conference on Artifical Intelligence (IBERAMIA 02) 
8th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2002 
Resumen: In this paper we present a habituation mechanism which includes a modification of the Stanley's habituation model with the addition of a stage based on spectrogram to detect temporal patterns in a signal and to obtain a measure of habituation to these patterns. This means that this measure shows a saturation process as the pattern is perceived by the system and when it disappears the measure drops. The use of the spectrogram simplifies the detection of the temporal patterns which can be detected with naive techniques. We have carried on some experiments both a synthetic signal and real signals like readings of a sonar in a mobile robot.
URI: http://hdl.handle.net/10553/42879
ISBN: 978-3-540-36131-2
354000131X
9783540001317
ISSN: 0302-9743
DOI: 10.1007/3-540-36131-6_91
Fuente: Garijo F.J., Riquelme J.C., Toro M. (eds) Advances in Artificial Intelligence — IBERAMIA 2002. IBERAMIA 2002. Lecture Notes in Computer Science, vol 2527. Springer, Berlin, Heidelberg
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