Advanced Digital Signal Processing and Noise Reduction / Edition 2by Saeed V. Vaseghi
Pub. Date: 01/28/2000
Signal processing plays an increasingly central role in the development of modern telecommunication and information processing systems, with a wide range of applications in areas such as multimedia technology, audio-visual signal processing, cellular mobile communication, radar systems and financial data forecasting. The theory and application of signal processing deals with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and hence, noise reduction and the removal of channel distortion is an important part of a signal processing system.
Advanced Digital Signal Processing and Noise Reduction, Third Edition, provides a fully updated and structured presentation of the theory and applications of statistical signal processing and noise reduction methods. Noise is the eternal bane of communications engineers, who are always striving to find new ways to improve the signal-to-noise ratio in communications systems and this resource will help them with this task.
Features two new chapters on Noise and Distortion and Noise in Wireless Communications. Topics discussed include: probability theory, Bayesian estimation and classification, hidden Markov models, adaptive filters, multi-band linear prediction, spectral estimation, and impulsive and transient noise removal. Explores practical solutions to interpolation of missing signals, echo cancellation, impulsive and transient noise removal, channel equalisation, HMM-based signal and noise decomposition. This is an invaluable text for senior undergraduates, postgraduates and researchers in the fields of digital signal processing,telecommunications and statistical data analysis. It will also appeal to engineers in telecommunications and audio and signal processing industries.
- Publication date:
- Edition description:
- Older Edition
- Product dimensions:
- 6.87(w) x 9.74(h) x 1.20(d)
Table of Contents
Noise and Distortion.
Hidden Markov Models.
Linear Prediction Models.
Power Spectrum and Correlation.
Transient Noise Pulses.
Channel Equalization and Blind Deconvolution.
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