ACM Home Page
Please provide us with feedback. Feedback
Low-power architectural trade-offs in a VLSI implementation of an adaptive hearing aid algorithm
Full text PdfPdf (643 KB)
Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 43rd annual conference on Design automation table of contents
San Francisco, CA, USA
SESSION: Session 33: low-power, thermal-aware architectures table of contents
Pages: 558 - 561  
Year of Publication: 2006
ISBN:1-59593-381-6
Authors
Felix Buergin  ETH Zurich, Zurich, Switzerland
Flavio Carbognani  ETH Zurich, Zurich, Switzerland
Martin Hediger  ETH Zurich, Zurich, Switzerland
Hektor Meier  ETH Zurich, Zurich, Switzerland
Robert Meyer-Piening  ETH Zurich, Zurich, Switzerland
Rafael Santschi  ETH Zurich, Zurich, Switzerland
Hubert Kaeslin  ETH Zurich, Zurich, Switzerland
Norbert Felber  ETH Zurich, Zurich, Switzerland
Wolfgang Fichtner  ETH Zurich, Zurich, Switzerland
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 50,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
Save this Article to a Binder    Display Formats: BibTex  EndNote ACM Ref   
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1146909.1147054
What is a DOI?

ABSTRACT

This paper analyzes the power-area trade-off of functionally equivalent architectural implementations of a speech enhancement algorithm for hearing aids. Gate-level simulations and measurements show that an optimum degree of resource sharing (0.60mW in a 0.25μm CMOS process) is more energy-efficient than both the fully time-multiplexed (1.42mW) and the isomorphic architecture (1.54mW), without overly large area overhead (0.77mm2 against 0.43mm2 and 4.31mm2, respectively).


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
S. Grassi. Optimized Implementation of Speech Processing Algorithms. University of Neuchâtel, Switzerland, 1998.
 
3
H. Kaeslin. VLSI I Lecture Notes on Architectures of Very Large Scale Integration Circuits. Microelectronics Design Center, Swiss Federal Institute of Technology, Zurich, Switzerland, 2005.
 
4
P. Mosch et al. A 660-μW 50-Mops 1-V DSP for a hearing aid chip set. IEEE Journal on Solid-State Circuits, 35(11):1705--1712, November 2000.
 
5
P. Ruiz-de Clavijo et al. Logic-level fast current simulation for digital cmos circuits. In Proceedings 15th International Workshop on Power and Timing Modeling, Optimization and Simulation (PATMOS 2005), pages 425--435, September 2005.
 
6
A. Schaub and P. Straub. Spectral sharpening for speech enhancement/noise reduction. In IEEE Acoustics, Speech and Signal Processing (ICASSP-91), pages 993--996, April 1991.
 
7
J. Wassner, H. Kaeslin, N. Felber, and W. Fichtner. Waveform coding for low-power digital filtering of speech data. IEEE Transactions on Signal Processing, 51(6):1656--1661, June 2003.

Collaborative Colleagues:
Felix Buergin: colleagues
Flavio Carbognani: colleagues
Martin Hediger: colleagues
Hektor Meier: colleagues
Robert Meyer-Piening: colleagues
Rafael Santschi: colleagues
Hubert Kaeslin: colleagues
Norbert Felber: colleagues
Wolfgang Fichtner: colleagues