Reservoir computing compensates slow response of chemosensor arrays exposed to fast varying gas concentrations in continuous monitoring

By Jordi Fonollosa, Sadique Sheik, Ramón Huerta, Santiago Marco. 2015

272 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering, Insect Science

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Citations in the corpus

Privacy-Preserving Distributed Linear Regression on High-Dimensional Data (2017, neutral): “7 · 102 26 58 9 Gas sensor array [27, 28] 16 4 208 261 4.”
Physical reservoir computing—an introductory perspective (2020, background): “Fonollosa et al. applied an RC framework to a chemical gas sensory system and showed that it is suitable for real-time and continuous monitoring applications and improves the time response of the chemical sensory system [26].”
Masked Autoregressive Flow for Density Estimation (2017, background): “ iis large enough to ensure that with high probability there are no identical values for the ith feature but small enough to not change the data values signiﬁcantly. GAS. Created by Fonollosa et al. [8], this dataset represents the readings of an array of 16 chemical sensors exposed to gas mixtures ”
Kalman-Based Stochastic Gradient Method with Stop Condition and Insensitivity to Conditioning (2015, methodology): “Three problem were experimented on: a linear regression problem on medical claims payment by CMS [16, 30], an additive nonparametric Haar wavelet regression problem on gas sensor readings [32, 15], and a logistic regression problem on adult income classification [33, 21].”
Neuron Clustering for Mitigating Catastrophic Forgetting in Supervised and Reinforcement Learning (2015, methodology): “For the second catastrophic forgetting test in which covariance was incorporated into the distance calculation, a dataset was utilized that consists of readings from a gas sensor array under dynamic gas mixtures [70].”
Sequential Covariance-Matrix Estimation with Application to Mitigating Catastrophic Forgetting (2015, methodology): “Experiment with Gas Sensor Array Dataset For the second catastrophic forgetting test, a dataset was utilized that consists of readings from a gas sensor array under dynamic gas mixtures [22].”
Optimal subsampling for quantile regression in big data (2020, methodology): “This data set was used to develop and test strategies for continuously monitoring or improving response time of chemical sensory systems (Fonollosa et al., 2015).”