Narrowband signal processing techniques with applications to distortion product otoacoustic emissions.

by Ma Wing-Kin.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 121-124).Chapter 1 --- Introduction to Otoacoustic Emissions --- p.1Chapter 1.1 --- Introduction --- p.1Chapter 1.2 --- Clinical Significance of the OAEs --- p.2Chapter 1.3 --- Classes of OAEs --- p.3Chapter 1.4 --- The Distortion Product OAEs --- p.4Chapter 1.4.1 --- Measurement of DPOAEs --- p.5Chapter 1.4.2 --- Some Properties of DPOAEs --- p.8Chapter 1.4.3 --- Noise Reduction of DPOAEs --- p.8Chapter 1.5 --- Goal of this work and Organization of the Thesis --- p.9Chapter 2 --- Review to some Topics in Narrowband Signal Estimation --- p.11Chapter 2.1 --- Fourier Transforms --- p.12Chapter 2.2 --- Periodogram ´ؤ Classical Spectrum Estimation Method --- p.15Chapter 2.2.1 --- Signal-to-Noise Ratios and Equivalent Noise Bandwidth --- p.17Chapter 2.2.2 --- Scalloping --- p.18Chapter 2.3 --- Maximum Likelihood Estimation --- p.19Chapter 2.3.1 --- Finding of the ML Estimator --- p.19Chapter 2.3.2 --- Properties of the ML Estimator --- p.21Chapter 3 --- Review to Adaptive Notch/Bandpass Filter --- p.23Chapter 3.1 --- Introduction --- p.23Chapter 3.2 --- Filter Structure --- p.24Chapter 3.3 --- Adaptation Algorithms --- p.25Chapter 3.3.1 --- Least Squares Method --- p.25Chapter 3.3.2 --- Least-Mean-Squares Algorithm --- p.27Chapter 3.3.3 --- Recursive-Least-Squares Algorithm --- p.28Chapter 3.4 --- LMS ANBF Versus RLS ANBF --- p.31Chapter 3.5 --- the IIR filter Versus ANBF --- p.31Chapter 4 --- Fast RLS Adaptive Notch/Bandpass Filter --- p.33Chapter 4.1 --- Motivation --- p.33Chapter 4.2 --- Theoretical Analysis of Sample Autocorrelation Matrix --- p.34Chapter 4.2.1 --- Solution of Φ (n) --- p.34Chapter 4.2.2 --- Approximation of Φ (n) --- p.35Chapter 4.3 --- Fast RLS ANBF Algorithm --- p.37Chapter 4.4 --- Performance Study --- p.39Chapter 4.4.1 --- Relationship to LMS ANBF and Bandwidth Evaluation . --- p.39Chapter 4.4.2 --- Estimation Error of Tap Weights --- p.40Chapter 4.4.3 --- Residual Noise Power of Bandpass Output --- p.42Chapter 4.5 --- Simulation Examples --- p.43Chapter 4.5.1 --- Estimation of Single Sinusoid in Gaussian White Noise . --- p.43Chapter 4.5.2 --- Comparing the Performance of IIR Filter and ANBFs . . --- p.44Chapter 4.5.3 --- Harmonic Signal Enhancement --- p.45Chapter 4.5.4 --- Cancelling 50/60Hz Interference in ECG signal --- p.46Chapter 4.6 --- Simulation Results of Performance Study --- p.52Chapter 4.6.1 --- Bandwidth --- p.52Chapter 4.6.2 --- Estimation Errors --- p.53Chapter 4.7 --- Concluding Summary --- p.55Chapter 4.8 --- Appendix A: Derivation of Ts --- p.56Chapter 4.9 --- Appendix B: Derivation of XT(n)Λ(n)ΛT(n)X(n) --- p.56Chapter 5 --- Investigation of the Performance of two Conventional DPOAE Estimation Methods --- p.58Chapter 5.1 --- Motivation --- p.58Chapter 5.2 --- The DPOAE Signal Model --- p.59Chapter 5.3 --- Preliminaries to the Conventional Methods --- p.60Chapter 5.3.1 --- Conventional Method 1: Constrained Stimulus Generation --- p.60Chapter 5.3.2 --- Conventional Method 2: Windowing --- p.61Chapter 5.4 --- Performance Comparison --- p.63Chapter 5.4.1 --- Sidelobe Level Reduction --- p.63Chapter 5.4.2 --- Estimation Accuracy --- p.65Chapter 5.4.3 --- Noise Floor Level --- p.67Chapter 5.4.4 --- Additional Loss by Scalloping --- p.68Chapter 5.5 --- Simulation Study --- p.69Chapter 5.5.1 --- Sidelobe Suppressions of the Windows --- p.69Chapter 5.5.2 --- Mean Level Estimation --- p.70Chapter 5.5.3 --- Mean Squared Error Analysis --- p.71Chapter 5.6 --- Concluding Summary --- p.75Chapter 5.7 --- Discussion --- p.75Chapter 5.8 --- Appendix A: Cramer-Rao Bound of the DPOAE Level Estimation --- p.76Chapter 6 --- Theoretical Considerations of Maximum Likelihood Estimation for the DPOAEs --- p.77Chapter 6.1 --- Motivation --- p.77Chapter 6.2 --- Finding of the MLEs --- p.78Chapter 6.2.1 --- First Form: Joint Estimation of DPOAE and Artifact Pa- rameter --- p.79Chapter 6.2.2 --- Second Form: Artifact Cancellation --- p.80Chapter 6.3 --- Relationship of CM1 to MLE --- p.81Chapter 6.4 --- Approximating the MLE --- p.82Chapter 6.5 --- Concluding Summary --- p.84Chapter 6.6 --- Appendix A: Equivalent Forms for the Minimum Least Squares Error --- p.85Chapter 7 --- Optimum Estimator Structure and Artifact Cancellation Ap- proaches for the DPOAEs --- p.87Chapter 7.1 --- Motivation --- p.87Chapter 7.2 --- The Optimum Estimator Structure --- p.88Chapter 7.3 --- References and Frequency Offset Effect --- p.89Chapter 7.4 --- Artifact Canceling Algorithms --- p.92Chapter 7.4.1 --- Least-Squares Canceler --- p.93Chapter 7.4.2 --- Windowed-Fourier-Transform Canceler --- p.93Chapter 7.4.3 --- FRLS Adaptive Canceler --- p.95Chapter 7.5 --- Time-domain Noise Rejection --- p.97Chapter 7.6 --- Regional Periodogram --- p.98Chapter 7.7 --- Experimental Results --- p.99Chapter 7.7.1 --- Artifact Cancellation via External Reference --- p.99Chapter 7.7.2 --- Artifact Cancellation via Internal Reference --- p.99Chapter 7.7.3 --- Artifact Cancellation in presence of Transient Noise --- p.101Chapter 7.7.4 --- Illustrative Example: DPgrams --- p.102Chapter 7.8 --- Conclusion and Discussion --- p.111Chapter 7.9 --- Appendix A: Derivation of the Parabolic Interpolation Method . --- p.113Chapter 7.10 --- Appendix B: Derivation of Weighted-Least-Squares Canceler . . --- p.114Chapter 8 --- Conclusions and Future Research Directions --- p.118Chapter 8.1 --- Conclusions --- p.118Chapter 8.2 --- Future Research Directions --- p.119Bibliography --- p.12