Simplex Optimization of PCA-Based Infrared Expert Systems

This paper describes an improved principal component analysis-based infrared expert system. The simplex algorithm is used to optimize the feature weight spectrum, thereby increasing the separation of different classes of compounds. First, the classification of a two-class system is significantly improved. Analysis indicates that compounds having more than three classes can also be separated in a single step using the same approach. This can simplify the structural elucidation tree in an expert system. Also reported here are factors influencing optimization of the feature weight spectra, including the initial data matrix and the step size of the optimization.