By Steven L. Gay, Jacob Benesty
158 2. Wiener Filtering 159 three. Speech Enhancement through Short-Time Spectral amendment three. 1 Short-Time Fourier research and Synthesis 159 one hundred sixty three. 2 Short-Time Wiener clear out 161 three. three strength Subtraction three. four significance Subtraction 162 three. five Parametric Wiener Filtering 163 164 three. 6 evaluation and dialogue Averaging suggestions for Envelope Estimation 169 four. 169 four. 1 relocating standard one hundred seventy four. 2 Single-Pole Recursion one hundred seventy four. three Two-Sided Single-Pole Recursion four. four Nonlinear facts Processing 171 five. instance Implementation 172 five. 1 Subband filter out financial institution structure 172 173 five. 2 A-Posteriori-SNR Voice task Detector five. three instance one hundred seventy five 6. end a hundred seventy five half IV Microphone Arrays 10 Superdirectional Microphone Arrays 181 Gary W. Elko 1. advent 181 2. Differential Microphone Arrays 182 three. Array Directional achieve 192 four. optimum Arrays for Spherically Isotropic Fields 193 four. 1 greatest achieve for Omnidirectional Microphones 193 four. 2 greatest Directivity Index for Differential Microphones 195 four. three Maximimum Front-to-Back Ratio 197 four. four minimal height Directional reaction 2 hundred four. five Beamwidth 201 five. layout Examples 201 five. 1 First-Order Designs 202 five. 2 Second-Order Designs 207 five. three Third-Order Designs 216 five. four Higher-Order designs 221 6. optimum Arrays for Cylindrically Isotropic Fields 222 6. 1 greatest achieve for Omnidirectional Microphones 222 6. 2 optimum Weights for max Directional achieve 224 6. three resolution for optimum Weights for optimum Front-to-Back Ratio for Cylindrical Noise 225 7. Sensitivity to Microphone Mismatch and Noise 230 8.
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This is why LMS converges slowly when excited by highly colored signals like speech. 18). To effectively use this fact, the step size must be a function of a}. 19) we have changed the constant terms in the coefficient . J, to prt CT x the constant a and the factors La} appear in the denominator. 18) becomes 0< a < 2. 21) it is apparent that both the speed of convergence and the range of stability for a are independent of the excitation signal's power for NLMS. This, of course, does not fix the slow convergence of those modes with small eigenvalues.
Acoustic Signal Processing for Telecommunication by Steven L. Gay, Jacob Benesty