By Saeed V. Vaseghi
Chapter 1 advent (pages 1–28):
Chapter 2 Noise and Distortion (pages 29–43):
Chapter three likelihood types (pages 44–88):
Chapter four Bayesian Estimation (pages 89–142):
Chapter five Hidden Markov versions (pages 143–177):
Chapter 6 Wiener Filters (pages 178–204):
Chapter 7 Adaptive Filters (pages 205–226):
Chapter eight Linear Prediction versions (pages 227–262):
Chapter nine strength Spectrum and Correlation (pages 263–296):
Chapter 10 Interpolation (pages 297–332):
Chapter eleven Spectral Subtraction (pages 333–354):
Chapter 12 Impulsive Noise (pages 355–377):
Chapter thirteen temporary Noise Pulses (pages 378–395):
Chapter 14 Echo Cancellation (pages 396–415):
Chapter 15 Channel Equalization and Blind Deconvolution (pages 416–466):
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Extra info for Advanced Digital Signal Processing and Noise Reduction, Second Edition
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The signal x(m) may then be recovered by subtraction of an estimate of the noise from the noisy signal. 3 shows a two-input adaptive noise cancellation system for enhancement of noisy speech. In this system a directional microphone takes Noisy signal y(m) = x(m) +n(m) Noise α n(m+ τ ) –1 w0 ... 3 Configuration of a two-microphone adaptive noise canceller. 7 Applications of Digital Signal Processing as input the noisy signal x(m) + n(m) , and a second directional microphone, positioned some distance away, measures the noise α n(m + τ ) .
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