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Electronic Nose: Algorithmic Challenges

  • Lei Zhang
  • Fengchun Tian
  • David Zhang

Table of contents

  1. Front Matter
    Pages i-xv
  2. Overview

    1. Front Matter
      Pages 1-1
    2. Lei Zhang, Fengchun Tian, David Zhang
      Pages 3-9
    3. Lei Zhang, Fengchun Tian, David Zhang
      Pages 11-20
  3. E-Nose Odor Recognition and Prediction: Challenge I

    1. Front Matter
      Pages 21-21
    2. Lei Zhang, Fengchun Tian, David Zhang
      Pages 23-46
    3. Lei Zhang, Fengchun Tian, David Zhang
      Pages 47-60
    4. Lei Zhang, Fengchun Tian, David Zhang
      Pages 61-77
    5. Lei Zhang, Fengchun Tian, David Zhang
      Pages 79-93
    6. Lei Zhang, Fengchun Tian, David Zhang
      Pages 95-113
    7. Lei Zhang, Fengchun Tian, David Zhang
      Pages 115-131
  4. E-Nose Drift Compensation: Challenge II

    1. Front Matter
      Pages 133-133
    2. Lei Zhang, Fengchun Tian, David Zhang
      Pages 135-146
    3. Lei Zhang, Fengchun Tian, David Zhang
      Pages 147-171
    4. Lei Zhang, Fengchun Tian, David Zhang
      Pages 173-191
    5. Lei Zhang, Fengchun Tian, David Zhang
      Pages 193-208
    6. Lei Zhang, Fengchun Tian, David Zhang
      Pages 209-224
    7. Lei Zhang, Fengchun Tian, David Zhang
      Pages 225-245
  5. E-Nose Disturbance Elimination: Challenge III

    1. Front Matter
      Pages 247-247
    2. Lei Zhang, Fengchun Tian, David Zhang
      Pages 249-264
    3. Lei Zhang, Fengchun Tian, David Zhang
      Pages 265-278
    4. Lei Zhang, Fengchun Tian, David Zhang
      Pages 279-298
  6. E-Nose Discreteness Correction: Challenge IV

    1. Front Matter
      Pages 299-299
    2. Lei Zhang, Fengchun Tian, David Zhang
      Pages 301-321
    3. Lei Zhang, Fengchun Tian, David Zhang
      Pages 323-333
    4. Lei Zhang, Fengchun Tian, David Zhang
      Pages 335-339

About this book

Introduction

This book presents the key technology of electronic noses, and systematically describes how e-noses can be used to automatically analyse odours. Appealing to readers from the fields of artificial intelligence, computer science, electrical engineering, electronics, and instrumentation science, it addresses three main areas: First, readers will learn how to apply machine learning, pattern recognition and signal processing algorithms to real perception tasks. Second, they will be shown how to make their algorithms match their systems once the algorithms don’t work because of the limitation of hardware resources. Third, readers will learn how to make schemes and solutions when the acquired data from their systems is not stable due to the fundamental issues affecting perceptron devices (e.g. sensors).

In brief, the book presents and discusses the key technologies and new algorithmic challenges in electronic noses and artificial olfaction. The goal is to promote the industrial application of electronic nose technology in environmental detection, medical diagnosis, food quality control, explosive detection, etc. and to highlight the scientific advances in artificial olfaction and artificial intelligence.

The book offers a good reference guide for newcomers to the topic of electronic noses, because it refers to the basic principles and algorithms. At the same time, it clearly presents the key challenges – such as long-term drift, signal uniqueness, and disturbance – and effective and efficient solutions, making it equally valuable for researchers engaged in the science and engineering of sensors, instruments, chemometrics, etc.

Keywords

Electronic Nose Pattern Recognition Drift Compensation Odor Recognition Machine Learning Gas Sensing Machine Olfaction Artificial Intelligence Intelligent Nose Bionic Perception

Authors and affiliations

  • Lei Zhang
    • 1
  • Fengchun Tian
    • 2
  • David Zhang
    • 3
  1. 1.College of Microelectronics and Communication EngineeringChongqing UniversityChongqingChina
  2. 2.College of Microelectronics and Communication EngineeringChongqing UniversityChongqingChina
  3. 3.School of Science and EngineeringChinese University of Hong Kong (Shenzhen)ShenzhenChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-13-2167-2
  • Copyright Information Springer Nature Singapore Pte Ltd. 2018
  • Publisher Name Springer, Singapore
  • eBook Packages Computer Science
  • Print ISBN 978-981-13-2166-5
  • Online ISBN 978-981-13-2167-2
  • Buy this book on publisher's site