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 types (pages 227–262):
Chapter nine energy 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 brief 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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Additional info for Advanced Digital Signal Processing and Noise Reduction, Second Edition
The time-varying distance of the object can be expanded in a Taylor series as r ( t ) = r0 + rt + 1 2 1 3 rt + rt + 2! 3! 14) where r0 is the distance, r is the velocity, r is the acceleration etc. 17) This shift in frequency is known as the Doppler frequency. If the object is moving towards the radar then the distance r(t) is decreasing with time, r is negative, and an increase in the frequency is observed. 16 Illustration of a radar system. 21 Sampling and Analog–to–Digital Conversion object is moving away from the radar then the distance r(t) is increasing, r is positive, and a decrease in the frequency is observed.
PrenticeHall, Englewood Cliffs, NJ. V. W. (1989) Discrete-Time Signal Processing. Prentice-Hall, Englewood Cliffs, NJ. , LING F. L. (1992) Advanced Signal Processing. Macmillan, New York. R. and GOLD B. (1975) Theory and Applications of Digital Processing. Prentice-Hall, Englewood Cliffs, NJ. R. W. (1978) Digital Processing of Speech Signals. Prentice-Hall, Englewood Cliffs, NJ. L. (1991) Statistical Signal Processing: Detection, Estimation, and Time Series Analysis. Addison Wesley, Reading, MA.
The term coloured noise refers to any broadband noise with a non-white spectrum. For example most audiofrequency noise, such as the noise from moving cars, noise from computer fans, electric drill noise and people talking in the background, has a nonwhite predominantly low-frequency spectrum. Also, a white noise passing through a channel is “coloured” by the shape of the channel spectrum. 3. 2 (a) A pink noise signal and (b) its magnitude spectrum. 3 (a) A brown noise signal and (b) its magnitude spectrum.
Advanced Digital Signal Processing and Noise Reduction, Second Edition by Saeed V. Vaseghi