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Active Signal Processing: A Counter-intuitive Approach to Enhancing Signal-to-Noise Ratio via Noise Injection

Published online by Cambridge University Press:  01 February 2011

Thomas George ,
Sandeep Gulati ,
Shahar Ben Menahem ,
James K Breaux ,
Cecilie Boysen ,
Vijay Daggumati  and
Ronald Quon
Thomas George
Affiliation:
[email protected], VIalogy Corporation, Product Development, 2400 Lincoln Avenue, Altadena, CA, 91001, United States, 626 296-6270, 626 296 6329
Sandeep Gulati
Affiliation:
[email protected], VIalogy Corporation, Product Development, 2400 Lincoln Avenue, Altadena, CA, 91001, United States, 626 296-6270, 626 296 6329
Shahar Ben Menahem
Affiliation:
[email protected], VIalogy Corporation, Product Development, 2400 Lincoln Avenue, Altadena, CA, 91001, United States, 626 296-6270, 626 296 6329
James K Breaux
Affiliation:
[email protected], VIalogy Corporation, Product Development, 2400 Lincoln Avenue, Altadena, CA, 91001, United States, 626 296-6270, 626 296 6329
Cecilie Boysen
Affiliation:
[email protected], VIalogy Corporation, Product Development, 2400 Lincoln Avenue, Altadena, CA, 91001, United States, 626 296-6270, 626 296 6329
Vijay Daggumati
Affiliation:
[email protected], VIalogy Corporation, Product Development, 2400 Lincoln Avenue, Altadena, CA, 91001, United States, 626 296-6270, 626 296 6329
Ronald Quon
Affiliation:
[email protected], VIalogy Corporation, Product Development, 2400 Lincoln Avenue, Altadena, CA, 91001, United States, 626 296-6270, 626 296 6329
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Abstract

Since its origin in the early 1980s, the noise-injection based stochastic resonance technique has spearheaded a novel counter-intuitive approach toward improving sensor performance. Within this approach, named Active Signal Processing, instead of removing system noise by filtering (Passive Signal Processing), it is possible to improve signal-to-noise ratio (SNR) by injecting noise into the measurement. ViaLogy LLC. has pioneered the development and demonstration of Quantum Resonance Interferometry (QRI), a quantum stochastic resonance (QSR)-based technique for improving SNR. The core of QRI processing involves the QSR-based generation of a Quantum Expressor Function (QEF), which characterizes the system of interest by encoding within it the noise environment, minimum level of detection, and the precision of measurement. Using digital post-processing of sensor information, QRI can determine the presence of a signal by the destruction of the resonance condition responsible for generating the system QEF. For applications aimed at detecting the presence of a weak signal, the strength of the signal is proportional to the number of iterations of the algorithm required for destruction of the resonance; the fewer the iterations, the stronger the signal. The application of QRI for detecting the presence of weakly expressing genes in fluorescent DNA microarrays will be described.

Keywords

nanoscalebiologicalsimulation
Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 952: Symposium F – Integrated Nanosensors , 2006 , 0952-F01-07
Copyright
Copyright © Materials Research Society 2007

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References

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