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 ...