DocumentCode :
1322591
Title :
Nonlinear system identification by m-pulse sequences: application to brainstem auditory evoked responses
Author :
Shi, Ying ; Hecox, Kurt E.
Author_Institution :
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Volume :
38
Issue :
9
fYear :
1991
Firstpage :
834
Lastpage :
845
Abstract :
A method is introduced for characterizing the nonlinear behavior of the auditory system. The method uses an m-pulse sequence as the stimulus and uses a general nonlinear framework for the auditory system. Like E.E. Sutter´s (1987) binary m-sequence approach, the m-pulse sequence approach is computationally efficient since calculation of the first-order input-output cross-correlation function is all that is necessary for obtaining the nonlinear characteristics of the system. The nonlinear system characteristics are reflected in pulse kernels in contrast to binary kernels associated with the binary m-sequence approach. By assuming the system under study is a third-order nonlinear system, binary and pulse kernels are shown to be related to Volterra kernels. The results suggest that the m-pulse sequence can be used to study the system nonlinear effects of varying the stimulus repetition rate more effectively then conventional methods. Preliminary physiological data obtained by applying m-pulse sequences to the brainstem auditory evoked responses (BAER) clearly illustrate the feasibility of obtaining replicable evoked response using this method.
Keywords :
bioelectric potentials; brain; hearing; identification; Volterra kernels; binary kernels; brainstem auditory evoked responses; first-order input-output cross-correlation function; m-pulse sequences; nonlinear system identification; physiological data; pulse kernels; third-order nonlinear system; Auditory system; Biological systems; Convolution; Kernel; Linear systems; Linearity; Nonlinear distortion; Nonlinear systems; System identification; White noise; Evoked Potentials, Auditory, Brain Stem; Humans; Models, Biological; Reference Values; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.83603
Filename :
83603
Link To Document :
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