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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2466

Title: A committee machine gas identification system based on dynamically reconfigurable FPGA
Authors: Shi, M
Bermak, A
Chandrasekaran, S
Amira, A
Brahim-Belhouari, S
Keywords: Committee machine (CM)
Dynamically reconfigurable field programmable gate array (FPGA)
Gas identification
Pattern recognition
Publication Date: 2008
Publisher: IEEE
Citation: IEEE Sensors Journal, 8(4): 403 - 414
Abstract: This paper proposes a gas identification system based on the committee machine (CM) classifier, which combines various gas identification algorithms, to obtain a unified decision with improved accuracy. The CM combines five different classifiers: K nearest neighbors (KNNs), multilayer perceptron (MLP), radial basis function (RBF), Gaussian mixture model (GMM), and probabilistic principal component analysis (PPCA). Experiments on real sensors' data proved the effectiveness of our system with an improved accuracy over individual classifiers. Due to the computationally intensive nature of CM, its implementation requires significant hardware resources. In order to overcome this problem, we propose a novel time multiplexing hardware implementation using a dynamically reconfigurable field programmable gate array (FPGA) platform. The processing is divided into three stages: sampling and preprocessing, pattern recognition, and decision stage. Dynamically reconfigurable FPGA technique is used to implement the system in a sequential manner, thus using limited hardware resources of the FPGA chip. The system is successfully tested for combustible gas identification application using our in-house tin-oxide gas sensors.
URI: http://bura.brunel.ac.uk/handle/2438/2466
DOI: http://dx.doi.org/10.1109/JSEN.2008.917124
ISSN: 1530-437X
Appears in Collections:School of Engineering and Design Research papers
Electronic and Computer Engineering

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