Titlebook: Electronic Nose: Algorithmic Challenges; Lei Zhang,Fengchun Tian,David Zhang Book 2018 Springer Nature Singapore Pte Ltd. 2018 Electronic

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角斗士

Paul R. Ferguson,Glenys J. Fergusonrift and interference problem of E-nose. The framework consists of two parts: (1) domain correction (DC) that makes the distributions of two domains close; (2) adaptive extreme learning machine (AELM) that learns a transferable classifier at decision level. This method is motivated by the idea of tr

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Invention, Innovation and Diffusion, for each sensor may be extracted; second, consider that the manual labeling of artificial olfaction data in real-time detection is difficult and hardly impossible, semi-supervised learning strategy is expected to be a breakthrough and overcome the problem of insufficient labeled data in artificial