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Electronic Nose: Algorithmic Challenges

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 add...

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Main Authors: Zhang, Lei. (Author, http://id.loc.gov/vocabulary/relators/aut), Tian, Fengchun. (http://id.loc.gov/vocabulary/relators/aut), Zhang, David. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Subjects:
Pattern recognition.
Biometrics (Biology).
Bioinformatics.
Health informatics.
Pattern Recognition.
Biometrics.
Computational Biology/Bioinformatics.
Health Informatics.
Online Access:https://doi.org/10.1007/978-981-13-2167-2
Table of Contents:
  • Part 1 : Overview
  • Chapter 1. Introduction
  • Chapter 2. Literature Review
  • Part 2 : E-nose Odor Recognition and Prediction: Challenge I
  • Chapter 3. Heuristic and Bio-inspired Neural Network Model
  • Chpater 4. Chaos based Neural Network Optimization Approach
  • Chapter 5. Multilayer Perceptrons based Concentration Estimation, etc.

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