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J. Low Power Electron. Appl. 2011, 1(1), 45-58; https://doi.org/10.3390/jlpea1010045

A Low-Power Hardware-Friendly Binary Decision Tree Classifier for Gas Identification

Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology (HKUST), Clear Water Bay, Kowloon, Hong Kong, China
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Received: 13 December 2010 / Revised: 1 March 2011 / Accepted: 2 March 2011 / Published: 9 March 2011
(This article belongs to the Special Issue Selected Topics in Low Power Design - From Circuits to Applications)
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Abstract

In this paper, we present a hardware friendly binary decision tree (DT) classifier for gas identification. The DT classifier is based on an axis-parallel decision tree implemented as threshold networks—one layer of threshold logic units (TLUs) followed by a programmable binary tree implemented using combinational logic circuits. The proposed DT classifier circuit removes the need for multiplication operation enabling up to 80% savings in terms of silicon area and power compared to oblique based-DT while achieving 91.36% classification accuracy without throughput degradation. The circuit was designed in 0.18 μm Charter CMOS process and tested using a data set acquired with in-house fabricated tin-oxide gas sensors. View Full-Text
Keywords: binary decision tree; classifier; gas identification; hardware implementation binary decision tree; classifier; gas identification; hardware implementation
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Li, Q.; Bermak, A. A Low-Power Hardware-Friendly Binary Decision Tree Classifier for Gas Identification. J. Low Power Electron. Appl. 2011, 1, 45-58.

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