Related Experiment Video
Updated: Feb 12, 2026

Fruit Volatile Analysis Using an Electronic Nose
Published on: March 30, 2012
Study on Interference Suppression Algorithms for Electronic Noses: A Review
Zhifang Liang1, Fengchun Tian2, Simon X Yang3
1College of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongwen Road 2nd, Nan'an District, Chongqing 400065, China. liangzf@cqupt.edu.cn.
Abstract:
Electronic noses (e-nose) are composed of an appropriate pattern recognition system and a gas sensor array with a certain degree of specificity and broad spectrum characteristics. The gas sensors have their own shortcomings of being highly sensitive to interferences which has an impact on the detection of target gases. When there are interferences, the performance of the e-nose will deteriorate. Therefore, it is urgent to study interference suppression techniques for e-noses. This paper summarizes the sources of interferences and reviews the advances made in recent years in interference suppression for e-noses. According to the factors which cause interference, interferences can be classified into two types: interference caused by changes of operating conditions and interference caused by hardware failures. The existing suppression methods were summarized and analyzed from these two aspects. Since the interferences of e-noses are uncertain and unstable, it can be found that some nonlinear methods have good effects for interference suppression, such as methods based on transfer learning, adaptive methods, etc.
Related Concept Videos
Interference and Diffraction
RNA Interference
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
Review and Preview
Percentiles are a type of fractile that partition data into...
Review and Preview
Nose and Nasal Cavity
Trial and Error and Algorithm

