TY - BOOK ID - 33060183 TI - Electronic Nose: Algorithmic Challenges AU - Zhang, Lei. AU - Tian, Fengchun. AU - Zhang, David. PY - 2018 SN - 9811321663 9811321671 PB - Singapore : Springer Singapore : Imprint: Springer, DB - UniCat KW - Olfactory sensors. KW - Gas detectors. KW - Intelligent sensors. KW - Smart sensors KW - Detectors KW - Chemical detectors KW - Odor sensors KW - Smell KW - Optical pattern recognition. KW - Biometrics. KW - Bioinformatics. KW - Medical records KW - Pattern Recognition. KW - Computational Biology/Bioinformatics. KW - Health Informatics. KW - Data processing. KW - EHR systems KW - EHR technology KW - EHRs (Electronic health records) KW - Electronic health records KW - Electronic medical records KW - EMR systems KW - EMRs (Electronic medical records) KW - Information storage and retrieval systems KW - Bio-informatics KW - Biological informatics KW - Biology KW - Information science KW - Computational biology KW - Systems biology KW - Optical data processing KW - Pattern perception KW - Perceptrons KW - Visual discrimination KW - Medical care KW - Data processing UR - https://www.unicat.be/uniCat?func=search&query=sysid:33060183 AB - 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. ER -