| 期刊全称 | Biologically Inspired Signal Processing for Chemical Sensing |
| 影响因子2023 | Agustín Gutiérrez,Santiago Marco |
| 视频video | http://file.papertrans.cn/188/187524/187524.mp4 |
| 发行地址 | Presents recent research in Biologically inspired signal and data processing.Includes supplementary material: |
| 学科分类 | Studies in Computational Intelligence |
| 图书封面 |  |
| 影响因子 | Biologically inspired approaches for artificial sensing have been extensively applied to different sensory modalities over the last decades and chemical senses have been no exception. The olfactory system, and the gustatory system to a minor extent, has been regarded as a model for the development of new artificial chemical sensing s- tems. One of the main contributions to this field was done by Persaud and Dodd in 1982 when they proposed a system based on an array of broad-selective chemical sensors coupled with a pattern recognition engine. The array aimed at mimicking the sensing strategy followed by the olfactory system where a population of bro- selective olfactory receptor neurons encodes for chemical information as patterns of activity across the neuron population. The pattern recognition engine proposed was not based on bio-inspired but on statistical methods. This influential work gave rise to a new line of research where this paradigm has been used to build chemical sensing instruments applied to a wide range of odor detection problems. More recently, some researchers have proposed to extend the biological inspiration of this system also to the processing of the sensor ar |
| Pindex | Book 2009 |
|Archiver|手机版|小黑屋|
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