Abstract
We propose a neuromorphic architecture for real-time processing of acoustic transients in analog VLSI. We show how judicious normalization of a time-frequency signal allows an elegant and robust implementation of a correlation algorithm. The algorithm uses binary multiplexing instead of analog-analog multiplication. This removes the need for analog storage and analog-multiplication. Simulations show that the resulting algorithm has the same out-of-sample classification performance (∼93% correct) as a baseline template-matching algorithm.
| Original language | English (US) |
|---|---|
| Title of host publication | Advances in Neural Information Processing Systems |
| Publisher | Neural information processing systems foundation |
| Pages | 734-740 |
| Number of pages | 7 |
| ISBN (Print) | 0262100657, 9780262100656 |
| State | Published - 1997 |
| Event | 10th Annual Conference on Neural Information Processing Systems, NIPS 1996 - Denver, CO, United States Duration: Dec 2 1996 → Dec 5 1996 |
Other
| Other | 10th Annual Conference on Neural Information Processing Systems, NIPS 1996 |
|---|---|
| Country | United States |
| City | Denver, CO |
| Period | 12/2/96 → 12/5/96 |
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ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
- Signal Processing
Cite this
Bangs, clicks, snaps, thuds and whacks : An architecture for acoustic transient processing. / Pineda, Fernando J; Cauwenberghs, Gert; Edwards, R. Timothy.
Advances in Neural Information Processing Systems. Neural information processing systems foundation, 1997. p. 734-740.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Bangs, clicks, snaps, thuds and whacks
T2 - An architecture for acoustic transient processing
AU - Pineda, Fernando J
AU - Cauwenberghs, Gert
AU - Edwards, R. Timothy
PY - 1997
Y1 - 1997
N2 - We propose a neuromorphic architecture for real-time processing of acoustic transients in analog VLSI. We show how judicious normalization of a time-frequency signal allows an elegant and robust implementation of a correlation algorithm. The algorithm uses binary multiplexing instead of analog-analog multiplication. This removes the need for analog storage and analog-multiplication. Simulations show that the resulting algorithm has the same out-of-sample classification performance (∼93% correct) as a baseline template-matching algorithm.
AB - We propose a neuromorphic architecture for real-time processing of acoustic transients in analog VLSI. We show how judicious normalization of a time-frequency signal allows an elegant and robust implementation of a correlation algorithm. The algorithm uses binary multiplexing instead of analog-analog multiplication. This removes the need for analog storage and analog-multiplication. Simulations show that the resulting algorithm has the same out-of-sample classification performance (∼93% correct) as a baseline template-matching algorithm.
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UR - http://www.scopus.com/inward/citedby.url?scp=84898978868&partnerID=8YFLogxK
M3 - Conference contribution
SN - 0262100657
SN - 9780262100656
SP - 734
EP - 740
BT - Advances in Neural Information Processing Systems
PB - Neural information processing systems foundation
ER -