Detection Algorithms for the nano nose

Document Type

Conference Proceeding

Publication Date

2008

Publication Title

19th International Conference on Systems Engineering, 2008, ICSENG

Publisher

IEEE

First page number:

399

Last page number:

404

Abstract

The nano nose is an instrument with an array of nano sized optical sensors that produces digital patterns when exposed to radiation passing through a gaseous mixture. This paper outlines an algorithm using a combination of neural networks and partial least squares (PLS) regression, Kalman filter capable of processing these digital patterns and generate an output. This output would not only show the detection of the individual constituents in the gaseous mixture but also the prediction of their concentrations. The developed algorithm in the experiments conducted, has performed detection and prediction of quite low concentrations of constituent gases successfully with a prediction error of less than 10% in the presence of noise.

Keywords

Gas detectors; Neural networks (Computer science); Optical detectors; Sensor networks

Disciplines

Other Computer Engineering | Other Electrical and Computer Engineering

Language

English

Permissions

Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited

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