This book presents a broad range of theory and application of statistical signal processing. The emphasis is on digital noise reduction algorithms, particularly important in the field of mobile communication. Vaseghi covers a broad range of applications, including spectral estimation, channel equalization, speech coding over noisy channels, active noise control, echo cancellation, and more.
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Signal processing and noise reduction are at the core of telecommunications and information processing systems. With the increasing use of digital cellular mobile systems in a variety of adverse environments, noise reduction is becoming a particularly important aspect of communication system design. This second edition provides a thoroughly revised and expanded introduction to the fundamentals of random processes, Bayesian modelling, and noise reduction. The subject is covered in a graphical and mathematically accessible manner with the emphasis on Bayesian inference and its application to noise reduction.
* Offers a comprehensive insight into a broad range of theory and applications of advanced signal processing
* Presents new chapters and sections on definition and modelling of different types of noise and distortions, multi-band linear prediction models, state-dependent Wiener filters and HMM-based noise reduction
* Explores practical solutions to echo cancellation, impulsive and transient noise removal, broad-band noise removal, channel equalisation, HMM-based signal and noise decomposition.
* Discusses topics such as probability theory, Bayesian estimation and classification, hidden Markov models, adaptive filters, multi-band linear prediction, spectral estimation and impulsive and transient noise removal
For professional engineers in telecommunications and audio and signal processing industries this updated second edition will be a valuable resource. Researchers and postgraduates in the fields of digital signal processing, statistical data analysis and telecommunications will also benefit from this extensive reference.
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