Advancement of three chemometric tools: network architecture, unsupervised learning and nonlinear feature extraction

In this paper, a recursive approach to network architecture optimization, an unsupervised learning backpropagation (ULBP) algorithm and a nonlinear discriminant feature extraction backpropagation (DFEBP) algorithm are proposed. Results of real-world chemical problems are presented.