Date of Award
1990
Document Type
Thesis
Publication Status
Version of Record
Submission Date
October 2026
Thesis/Dissertation Advisor [Chair]
Erdol, Nurgun
Abstract
The cochlea provides frequency selectivity for acoustic input signal processing in mammals. The excellent performance of human hearing for speech processing leads to examination of the cochlea as a paradigm for signal processing. The components of the hearing process are examined and suitable models are selected for each component's function. The signal processing function is simulated by a computer program and the ensemble is examined for behavior and improvement. The models reveal that the motion of the basilar membrane provides a very selective low pass transmission characteristic. Narrowband frequency resolution is obtained from the motion by computation of spatial differences in the magnitude of the motion as energy propagates along the membrane. Basilar membrane motion is simulated using the integrable model of M. R. Schroeder, but the paradigm is useful for any model that exhibits similar high selectivity. Support is shown for an hypothesis that good frequency discrimination is possible without highly resonant structure. The nonlinear magnitude calculation is performed on signals developed without highly resonant structure, and differences in those magnitudes are signals shown to have good narrowband selectivity. Simultaneously, good transient behavior is preserved due to the avoidance of highly resonant structure. The cochlear paradigm is shown to provide a power spectrum with serendipitous good frequency selectivity and good transient response simultaneously.
Extent
214 p.
Recommended Citation
Barrett, Raymond L Jr, "cochlea: A signal processing paradigm" (1990). Electronic Theses and Dissertations 1990 - 1999. 14.
https://digitalcommons.fau.edu/etd_general_4/14
Identifier
FADT12251
Comments
College of Engineering and Computer Science|FAU Electronic Theses and Dissertations Collection|Thesis (Ph.D.)--Florida Atlantic University, 1990.|College of Engineering and Computer Science