DocumentCode
1682476
Title
Learning of sparse auditory receptive fields
Author
Körding, Konrad P. ; König, Peter ; Klein, David J.
Author_Institution
Inst. of Neuroinformatics, ETH/UNI Zurich, Switzerland
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1103
Lastpage
1108
Abstract
It is largely unknown how the properties of the auditory system relate to the properties of natural sounds. Here, we analyze representations of simulated neurons that have optimally sparse activity in response to spectro-temporal speech data. These representations share important properties with the auditory neurons determined in electrophysiological experiments
Keywords
hearing; learning (artificial intelligence); neural nets; neurophysiology; auditory neurons; auditory receptive fields; auditory system; learning; simulated neurons; sparse activity; spectral temporal speech data; Analytical models; Auditory system; Frequency; Layout; Mathematical model; Neurons; Principal component analysis; Spectrogram; Speech analysis; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1007648
Filename
1007648
Link To Document