CHARACTERISTICS OF BACKPROPAGATION NEURAL NETWORKS EMPLOYED IN THE IDENTIFICATION OF NEUROTRANSMITTER RAMAN-SPECTRA

We have shown that neural networks are capable of accurately identifyi ng the Raman spectra of aqueous solutions of small-molecule neurotrans mitters. It was found that the networks performed optimally when the r atio of the number of hidden nodes to the number of input nodes was 0. 16, that network accuracy increased with the number of input layer nod es, and that input features influenced the abilities of networks to di scriminate or generalize between spectra. Furthermore, networks employ ing sine transfer functions for their hidden layers trained faster and were better at discriminating between closely related spectra, but th ey were less tolerant of spectral distortions than the networks using sigmoid transfer functions. The latter type of network produced superi or results where generalization between spectra was required.