DocumentCode :
2991631
Title :
2-D spatial frequency dependence of VEPs: A neural network analysis
Author :
Iezzi, Raymond, Jr. ; Micheli-Tzanakou, Evangelia
Author_Institution :
Dept. of Biomed. Eng., Rutgers Univ., New Brunswick, NJ, USA
fYear :
1993
fDate :
18-19 Mar 1993
Firstpage :
111
Lastpage :
112
Abstract :
An approach to black-box identification-function problems is introduced. Visual evoked potentials (VEPs) were recorded from normal subjects using stimulus patterns that evolved from a totally random distribution of intensities to an ordered distribution representing a bar. The contribution of all spatial frequencies to the amplitudes of the evoked potentials was studied by performing a 2-D FFT on the stimulus images. The FFT spectra were used as inputs to a neural network as a black box approach in order to study the VEP spatial frequency tuning curves of the subjects
Keywords :
fast Fourier transforms; medical image processing; multilayer perceptrons; visual evoked potentials; 2-D FFT; 2-D spatial frequency dependence; ALOPEX; black-box identification-function problems; neural network analysis; stimulus patterns; visual evoked potentials; Biomedical engineering; Biomedical imaging; Educational institutions; Equations; Frequency conversion; Frequency dependence; Gratings; Image converters; Neural networks; Tuning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioengineering Conference, 1993., Proceedings of the 1993 IEEE Nineteenth Annual Northeast
Conference_Location :
Newark, NJ
Print_ISBN :
0-7803-0925-1
Type :
conf
DOI :
10.1109/NEBC.1993.404396
Filename :
404396
Link To Document :
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