DocumentCode
2351706
Title
Evaluation of neural classifiers using statistic methods for identification of laryngeal pathologies
Author
de O.Rosa, M. ; Pereira, Jose Casimiro ; Carvalho, C. P L F
Author_Institution
Escola de Engenharia, Sao Paulo Univ., Brazil
fYear
1998
fDate
9-11 Dec 1998
Firstpage
220
Lastpage
225
Abstract
The use of statistical elements, like nonparametric tests and principal components analysis, allows the evaluation of the behavior and the performance of artificial neural networks when acoustical measurements are used to identify larynx diseases from which patterns are naturally overlapped. In this work, techniques to improve the results of neural network through the manipulation of the training patterns and convergence control will be discussed
Keywords
acoustic signal processing; diseases; medical diagnostic computing; medical expert systems; medical signal processing; pattern classification; statistical analysis; PCA; acoustical measurements; convergence control; laryngeal pathology identification; larynx diseases; neural classifier evaluation; nonparametric tests; principal components analysis; statistical elements; statistical methods; training patterns; Acoustic measurements; Cancer; Diseases; Frequency; Jitter; Larynx; Pathology; Power harmonic filters; Speech; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1998. Proceedings. Vth Brazilian Symposium on
Conference_Location
Belo Horizonte
Print_ISBN
0-8186-8629-4
Type
conf
DOI
10.1109/SBRN.1998.731033
Filename
731033
Link To Document