Shouxin Ren

According to our database1, Shouxin Ren authored at least 10 papers between 2008 and 2013.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Links

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Bibliography

2013
Resolution of overlapping fluorescence spectra using the kernel learning machine.
Proceedings of the Ninth International Conference on Natural Computation, 2013

2012
Simultaneous multicomponent polycyclic aromatic hydrocarbon analysis using an independent component analysis-based latent variable regression.
Proceedings of the Eighth International Conference on Natural Computation, 2012

Combining blind source analysis and Elman recurrent neural network to determine overlapping voltammograms.
Proceedings of the Eighth International Conference on Natural Computation, 2012

Simultaneous multicomponent organic compound analysis using two intelligent signal processing methods.
Proceedings of the 5th International Conference on BioMedical Engineering and Informatics, 2012

2011
Resolve of Multicomponent Mixtures Using Voltammetry and a Hybrid Artificial Neural Network Method.
Proceedings of the Artificial Intelligence and Computational Intelligence, 2011

Simultaneous Multicomponent Spectrophotometric Kinetic Determination by a Hybrid Intelligent Computing Method.
Proceedings of the Artificial Intelligence and Computational Intelligence, 2011

2009
Linking Direct Orthogonal Signal Correction and Wavelet Transform with Radial Basis Function Neural Network to Analyze Overlapping Spectra.
Proceedings of the Second International Workshop on Knowledge Discovery and Data Mining, 2009

Improvement of Prediction Ability of Multicomponent Regression Model by a Method Based on Data Mining in Chemometrics.
Proceedings of the Second International Workshop on Knowledge Discovery and Data Mining, 2009

2008
The Speciation of Iron by a Wavelet Packet Transform Based Generalized Regression Neural Network.
Proceedings of the Fourth International Conference on Natural Computation, 2008

Multicomponent Kinetic Determination Using an Artificial Neural Network with Maximum Likelihood Principal Component Analysis.
Proceedings of the Fourth International Conference on Natural Computation, 2008


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