Brainstem auditory evoked potential classification by backpropagation networks

D. Alpsan, O. Ozdamar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

A feedforward neural network with one hidden layer is applied to the problem of brainstem auditory evoked potential classification. Network performances were tested separately both on subject-dependent samples (drawn from the same subjects from which the training set was derived) and on subject-independent samples (drawn from subjects from which no data were included in the training set), and compared. The results indicate that, while increasing the training set size improves performance, human-selected training sets give better results than randomly selected sets. Different encoding schemes used for representing the signal yield varying rates of correct recognition. Although the networks were overly complex and trained in the memorization mode, they show some feature extracting and generalization capabilities.

Original languageEnglish (US)
Title of host publication91 IEEE Int Jt Conf Neural Networks IJCNN 91
PublisherPubl by IEEE
Pages1266-1271
Number of pages6
ISBN (Print)0780302273, 9780780302273
DOIs
StatePublished - 1991
Event1991 IEEE International Joint Conference on Neural Networks - IJCNN '91 - Singapore, Singapore
Duration: Nov 18 1991Nov 21 1991

Publication series

Name91 IEEE Int Jt Conf Neural Networks IJCNN 91

Other

Other1991 IEEE International Joint Conference on Neural Networks - IJCNN '91
CitySingapore, Singapore
Period11/18/9111/21/91

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Alpsan, D., & Ozdamar, O. (1991). Brainstem auditory evoked potential classification by backpropagation networks. In 91 IEEE Int Jt Conf Neural Networks IJCNN 91 (pp. 1266-1271). (91 IEEE Int Jt Conf Neural Networks IJCNN 91). Publ by IEEE. https://doi.org/10.1109/ijcnn.1991.170571