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Principal Component‐Wavelet Neural Networks as a New Multivariate Calibration Method

Authors: T Khayamian, Ali A Ensafi, R Tabaraki, M Esteki
Publication date: 2005/7/1
Journal name: Analytical letters
Volume: 38
Issue: 9
Pages: 1477-1489
Publisher: Taylor & Francis Group
 
Abstract A principal component‐wavelet neural network (PC‐WNN) was proposed as a
multivariate calibration method for simultaneous determination of test samples of copper,
iron, and aluminum. Principal component analysis has been applied to the data set for
dimensionality reduction of the data matrix, and neural network with wavelet function has
been employed as the function‐learning method. The data sets consisted of 27 standard
solutions, which were randomly divided into training and prediction sets. The WNN ...

http://www.tandfonline.com/doi/abs/10.1081/AL-200062265

Journal Papers
Month/Season: 
July
Year: 
2005

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