Advanced digital signal processing and noise reduction Saeed V. Vaseghi.

By: Vaseghi, Saeed VMaterial type: TextTextPublisher: Chichester, U.K. : J. Wiley & Sons, 2008Edition: 4th edDescription: xxx, 514 p. : ill. ; 25 cmISBN: 9780470754061 (cloth); 0470754060 (cloth)Subject(s): Signal processing | Electronic noise | Digital filters (Mathematics)DDC classification: 621.3822 Online resources: Table of contents only
Contents:
Introduction -- Noise and Distortion -- Information Theory and Probability Models -- Bayesian Inference -- Hidden Markov Models -- Least Square Error Wiener-Kolmogorov Fillers -- Adaptive Filters: Kalman, RLS, LMS -- Linear Prediction Models -- Eigenvalue Analysis and Principal Component Analysis -- Power Spectrum Analysis -- Interpolation -- Replacement of Lost Samples -- Signal Enhancement via Spectral Amplitude Estimation -- Impulsive Noise: Modelling, Detection and Removal -- Transient Noise Pulses -- Echo Cancellation -- Channel Equalisation and Blind Deconvolution -- Speech Enhancement: Noise Reduction, Bandwidth Extension and Packet Replacement -- Multiple-Input Multiple-Output Systems, Independent Component Analysis -- Signal Processing in Mobile Communication.
Review: "Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system." "The 4th edition of Advanced Digital Signal Processing and Noise Reduction updates and extends the chapters in the previous edition and includes two new chapters on MIMO systems, Correlation and Eigen analysis and independent component analysis. The wide range of topics covered in this book include Wiener filters, echo cancellation, channel equalisation, spectral estimation, detection and removal of impulsive and transient noise, interpolation of missing data segments, speech enhancement and noise/interference in mobile communication environments. This book provides a coherent and structured presentation of the theory and applications of statistical signal processing and noise reduction methods."--Jacket.
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Book Book Central Library (CL)
Central Library (CL)
NFIC General Stacks 621.3822 VAS (Browse shelf) Available SEECS012187
Total holds: 0

Includes bibliographical references and index.

1. Introduction -- 2. Noise and Distortion -- 3. Information Theory and Probability Models -- 4. Bayesian Inference -- 5. Hidden Markov Models -- 6. Least Square Error Wiener-Kolmogorov Fillers -- 7. Adaptive Filters: Kalman, RLS, LMS -- 8. Linear Prediction Models -- 9. Eigenvalue Analysis and Principal Component Analysis -- 10. Power Spectrum Analysis -- 11. Interpolation -- Replacement of Lost Samples -- 12. Signal Enhancement via Spectral Amplitude Estimation -- 13. Impulsive Noise: Modelling, Detection and Removal -- 14. Transient Noise Pulses -- 15. Echo Cancellation -- 16. Channel Equalisation and Blind Deconvolution -- 17. Speech Enhancement: Noise Reduction, Bandwidth Extension and Packet Replacement -- 18. Multiple-Input Multiple-Output Systems, Independent Component Analysis -- 19. Signal Processing in Mobile Communication.

"Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system." "The 4th edition of Advanced Digital Signal Processing and Noise Reduction updates and extends the chapters in the previous edition and includes two new chapters on MIMO systems, Correlation and Eigen analysis and independent component analysis. The wide range of topics covered in this book include Wiener filters, echo cancellation, channel equalisation, spectral estimation, detection and removal of impulsive and transient noise, interpolation of missing data segments, speech enhancement and noise/interference in mobile communication environments. This book provides a coherent and structured presentation of the theory and applications of statistical signal processing and noise reduction methods."--Jacket.

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