By Saeed V. Vaseghi
Chapter 1 advent (pages 1–28):
Chapter 2 Noise and Distortion (pages 29–43):
Chapter three likelihood versions (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 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 resources for Advanced Digital Signal Processing and Noise Reduction, Second Edition
18. 1 Time-Domain Sampling and Reconstruction of Analog Signals The conversion of an analog signal to a sequence of n-bit digits consists of two basic steps of sampling and quantisation. The sampling process, when performed with sufficiently high speed, can capture the fastest fluctuations of the signal, and can be a loss-less operation in that the analog signal can be recovered through interpolation of the sampled sequence as described in Chapter 10. The quantisation of each sample into an n-bit digit, involves some irrevocable error and possible loss of information.
2 Blind Channel Equalisation Channel equalisation is the recovery of a signal distorted in transmission through a communication channel with a non-flat magnitude or a non-linear phase response. When the channel response is unknown the process of signal recovery is called blind equalisation. Blind equalisation has a wide range of applications, for example in digital telecommunications for removal of inter-symbol interference due to non-ideal channel and multipath propagation, in speech recognition for removal of the effects of the microphones and the communication channels, in correction of distorted images, analysis of seismic data, de-reverberation of acoustic gramophone recordings etc.
A. (1963) Linear System Theory: The StateSpace Approach. McGraw-Hill, NewYork. Advanced Digital Signal Processing and Noise Reduction, Second Edition. Saeed V. 10 Thermal Noise Shot Noise Electromagnetic Noise Channel Distortions Modelling Noise oise can be defined as an unwanted signal that interferes with the communication or measurement of another signal. A noise itself is a signal that conveys information regarding the source of the noise. For example, the noise from a car engine conveys information regarding the state of the engine.