Electronic Nose: Algorithmic Challenges
暫譯: 電子鼻:演算法挑戰

Lei Zhang, Fengchun Tian, David Zhang

  • 出版商: Springer
  • 出版日期: 2018-09-22
  • 售價: $5,640
  • 貴賓價: 9.5$5,358
  • 語言: 英文
  • 頁數: 339
  • 裝訂: Hardcover
  • ISBN: 9811321663
  • ISBN-13: 9789811321665
  • 相關分類: Algorithms-data-structures
  • 海外代購書籍(需單獨結帳)

商品描述

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.

商品描述(中文翻譯)

本書介紹電子鼻的關鍵技術,並系統性地描述如何利用電子鼻自動分析氣味。該書吸引來自人工智慧、計算機科學、電機工程、電子學和儀器科學等領域的讀者,主要涵蓋三個方面:首先,讀者將學習如何將機器學習、模式識別和信號處理算法應用於實際感知任務。其次,當算法因硬體資源的限制而無法運作時,將展示如何使算法與系統相匹配。第三,讀者將學習如何在由於影響感知器件(例如傳感器)的基本問題而導致系統獲取的數據不穩定時制定方案和解決方案。

簡而言之,本書介紹並討論電子鼻和人工嗅覺中的關鍵技術及新算法挑戰。其目標是促進電子鼻技術在環境檢測、醫療診斷、食品質量控制、爆炸物檢測等領域的工業應用,並突顯人工嗅覺和人工智慧的科學進展。

本書為電子鼻主題的新手提供了良好的參考指南,因為它提及了基本原則和算法。同時,它清楚地呈現了關鍵挑戰,例如長期漂移、信號唯一性和干擾,以及有效且高效的解決方案,使其對從事傳感器、儀器、化學計量學等科學和工程研究的研究人員同樣具有價值。