Artificial neural network and classical least-squares methods for neurotransmitter mixture analysis.

@article{Schulze1995ArtificialNN,
  title={Artificial neural network and classical least-squares methods for neurotransmitter mixture analysis.},
  author={Hans Georg Schulze and L. Shane Greek and Boris B. Gorzalka and Annie Br{\'e}e and Michael W. Blades and Robin F B Turner},
  journal={Journal of neuroscience methods},
  year={1995},
  volume={56 2},
  pages={155-67}
}
Identification of individual components in biological mixtures can be a difficult problem regardless of the analytical method employed. In this work, Raman spectroscopy was chosen as a prototype analytical method due to its inherent versatility and applicability to aqueous media, making it useful for the study of biological samples. Artificial neural networks (ANNs) and the classical least-squares (CLS) method were used to identify and quantify the Raman spectra of the small-molecule… CONTINUE READING