Characteristics of Backpropagation Neural Networks Employed in the Identification of Neurotransmitter Raman Spectra

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Abstract:

We have shown that neural networks are capable of accurately identifying the Raman spectra of aqueous solutions of small-molecule neurotransmitters. It was found that the networks performed optimally when the ratio 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 nodes, and that input features influenced the abilities of networks to discriminate or generalize between spectra. Furthermore, networks employing sine transfer functions for their hidden layers trained faster and were better at discriminating between closely related spectra, but they were less tolerant of spectral distortions than the networks using sigmoid transfer functions. The latter type of network produced superior results where generalization between spectra was required.

Keywords: Artificial neural networks; Backpropagation networks; Discrimination; Generalization; Neurotransmitters; Raman spectra; Transfer function

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/0003702944027688

Affiliations: 1: Interdisciplinary Studies, The University of British Columbia, 237-6174 University Boulevard, Vancouver, B.C., V6T 1Z3 Canada 2: Department of Chemistry , The University of British Columbia, 237-6174 University Boulevard, Vancouver, B.C., V6T 1Z3 Canada 3: Department of Chemistry, The University of British Columbia, 237-6174 University Boulevard, Vancouver, B.C., V6T 1Z3 Canada 4: Department of Psychology, The University of British Columbia, 237-6174 University Boulevard, Vancouver, B.C., V6T 1Z3 Canada 5: Department of Electrical Engineering, The University of British Columbia, 237-6174 University Boulevard, Vancouver, B.C., V6T 1Z3 Canada 6: Biotechnology Laboratory and Department of Electrical Engineering, The University of British Columbia, 237-6174 University Boulevard, Vancouver, B.C., V6T 1Z3 Canada

Publication date: January 1, 1994

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