DocumentCode
2851786
Title
A Low-Power Haar-Wavelet Preprocessing Approach for a SNN Olfactory System
Author
Allen, Jacob N. ; Hasan, Safa B. ; Abdel-Aty-Zohdy, Hoda S. ; Ewing, Robert L.
Author_Institution
Oakland Univ. Rochester, Oakland
fYear
2007
fDate
16-18 Dec. 2007
Firstpage
222
Lastpage
225
Abstract
A low frequency and low power spiking neural network chip is designed to classify polymer film electronic nose patterns. A simulation model for polymer film chemical sensors is developed and compared to other approaches. The final chip design uses wavelet pre-processing for fault tolerance and operates at just 20 kHz.
Keywords
Haar transforms; chemioception; electronic noses; neural chips; pattern classification; polymer films; wavelet transforms; Haar-wavelet preprocessing; frequency 20 kHz; olfactory system; pattern classification; polymer film chemical sensor; polymer film electronic nose; spiking neural network chip; Analytical models; Chemical sensors; Electronic noses; Force sensors; Neural networks; Olfactory; Polymer films; Semiconductor device modeling; Sensor arrays; Substrates;
fLanguage
English
Publisher
ieee
Conference_Titel
Design and Test Workshop, 2007. IDT 2007. 2nd International
Conference_Location
Cairo
Print_ISBN
978-1-4244-1824-4
Electronic_ISBN
978-1-4244-1825-1
Type
conf
DOI
10.1109/IDT.2007.4437464
Filename
4437464
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