Journal Article10.1016/J.NEUNET.2015.07.014
Towards biological plausibility of electronic noses
Sankho Turjo Sarkar,Amol P. Bhondekar,Martin Macas,Ritesh Kumar,Rishemjit Kaur,Anupma Sharma,Ashu Gulati,Amod Kumar +7 more
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TL;DR: A novel encoding scheme for neuronal code generation for odour recognition using an electronic nose using multiple Gaussian receptive fields superimposed over the temporal EN responses is presented, demonstrating a biomimetic approach for EN data analysis.
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About: This article is published in Neural Networks. The article was published on 01 Nov 2015. The article focuses on the topics: Spiking neural network.
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Citations
Gas Recognition in E-Nose System: A Review
TL;DR: In this paper , the authors investigate several gas recognition methods for E-nose, and compare and analyze them in terms of algorithms and hardware implementations, and find each classical gas recognition method has a relatively fixed framework and a few parameters, which makes it easy to be designed and perform well with limited gas samples, but weak in multi-gas recognition under noise.
Determination of tea polyphenols in green tea by homemade color sensitive sensor combined with multivariate analysis.
TL;DR: The overall results sufficiently demonstrate that it is feasible to quantitative detect tea polyphenols content in green tea by the homemade color sensitive sensor combined with appropriate chemometrics methods.
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A Hardware-Deployable Neuromorphic Solution for Encoding and Classification of Electronic Nose Data
TL;DR: This investigation proposed a spiking neural network (SNN)-based classifier that can be seamlessly deployed on a neuromorphic system-on-a-chip (NSoC) that was determined to be able to classify real-valued sensor data with greater than 90% accuracy and with a maximum latency of 3 s on the software-based platform.
Cross-Category Tea Polyphenols Evaluation Model Based on Feature Fusion of Electronic Nose and Hyperspectral Imagery.
TL;DR: Results indicate that the proposed method can improve the estimation accuracy of tea polyphenol content for cross-category evaluation, which provides a technical basis for predicting other components of tea.
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References
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TL;DR: An electronic nose constructed using semiconductor transducers and incorporating design features suggested by the proposal can reproducibly discriminate between a wide variety of odours, and its properties show that discrimination in an olfactory system could be achieved without the use of highly specific receptors.
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