A low-power hardware-friendly binary decision tree classifier for gas identification

Qingzheng Li, Amine Bermak

Research output: Contribution to journalArticle

19 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)45-58
Number of pages14
JournalJournal of Low Power Electronics and Applications
Volume1
Issue number1
DOIs
Publication statusPublished - 9 Mar 2011
Externally publishedYes

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Keywords

  • Binary decision tree
  • Classifier
  • Gas identification
  • Hardware implementation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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