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Advanced Signal Processing and Noise Reduction, 2nd Edition
 
 
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Advanced Signal Processing and Noise Reduction, 2nd Edition [Hardcover]

Professor Saeed V. Vaseghi (Author)
2.7 out of 5 stars  See all reviews (3 customer reviews)

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Book Description

September 20, 2000 0471626929 978-0471626923 2
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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Editorial Reviews

From the Back Cover

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.

About the Author

Saeed Vaseghi is currently a Professor of Communications and Signal Processing at Brunel University’s department of Electronics and Computer Engineering and is Group Leader for the Communications & Multimedia Signal Processing Group.

Previously, Saeed obtained a first in Electrical and Electronics Engineering from Newcastle University, and a PhD in Digital Signal Processing from Cambridge University. His Ph.D. in noisy signal restoration led to establishment of CEDAR, the world's leading system for restoration of audio signals. Saeed also held a British Telecom lectureship at UEA Norwich, and a readership at Queen's University of Belfast before his move to Brunel. --This text refers to an out of print or unavailable edition of this title.


Product Details

  • Hardcover: 456 pages
  • Publisher: Wiley; 2 edition (September 20, 2000)
  • Language: English
  • ISBN-10: 0471626929
  • ISBN-13: 978-0471626923
  • Product Dimensions: 9.9 x 6.9 x 1.2 inches
  • Shipping Weight: 2.1 pounds (View shipping rates and policies)
  • Average Customer Review: 2.7 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #3,513,800 in Books (See Top 100 in Books)

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Customer Reviews

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Average Customer Review
2.7 out of 5 stars (3 customer reviews)
 
 
 
 
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8 of 8 people found the following review helpful:
2.0 out of 5 stars Good selection of material, superficial treatment, May 23, 2005
By 
D. Brown (Seattle, WA USA) - See all my reviews
(REAL NAME)   
This review is from: Advanced Signal Processing and Noise Reduction, 2nd Edition (Hardcover)
This is a book about digital signal processing noise reduction techniques. The selection of techniques covered is very broad, much more extensive than most books I have seen in this field.

Unfortunately, the book has some severe shortcomings. As another reviewer has mentioned, the treatment of each technique is too shallow to be useful, and the bibliography much less than helpful. A helpful bibliography for each section would refer to more extensive treatments that might be usable for design and implementation. The bibliography for each chapter is instead dated and nonspecific, consisting of a seemingly random collection of technical reports, papers, and books published over three or four decades.

The book is filled with equations, which are frustrating to read. They appear to have been typeset using a word processor that did not properly space mathematical symbols. For example, function parameters (in parentheses) are often closer to the following factor than the function name. The equations are often hard to read. The equations dealing with continuous functions are generally straightforward to interpret, but those dealing with discrete-time functions are frequently written with indices in parentheses instead of as subscripts. As you are reading through the mathematics, you have to separate in your mind the functions (with parameters) from the vector elements (with indices). The typesetting occasionally renders greek symbols in a bold font, so sometimes on the same page you will have the same symbols in different equations bolded or not bolded.

Another problem with the mathematics comes about because of the extensiveness of the material. Different signal processing techniques have different mathematical histories, and therefore different naming conventions. The author generally uses the conventional mathematical notation for each technique, leading to jarring transitions from section to section.

All in all, I think this could be a very useful book, if it were more carefully written, typeset adequately, if the treatment of each technique were better motivated and complete enough to use, and if the bibliography provided useful references to specialized treatments of individual topics.
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7 of 8 people found the following review helpful:
2.0 out of 5 stars Shallow, fragmented and dated., March 22, 2002
By A Customer
This review is from: Advanced Signal Processing and Noise Reduction, 2nd Edition (Hardcover)
The book's back cover claims that "Researchers and postgraduates in the fields of digital signal processing, statistical data analysis and telecommunications will also benefit from this extensive reference." I find this book very disappointing. Its signal processing development is unusually inexact even for beginning graduate students. Its exposition is often verbally vague and mathematically unrigorous, with rather shallow technical depth even for engineering students. Its theoretical framework seems fragmented. Its bibliography is dated and anecdotal. As an active researcher in this field, I would not recommend my colleagues to use this book.
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1 of 5 people found the following review helpful:
4.0 out of 5 stars A good book on noise reduction, August 29, 2001
By A Customer
This review is from: Advanced Signal Processing and Noise Reduction, 2nd Edition (Hardcover)
A good book on noise reduction and Wiener filter. But
you may need to read some papers afterwards. Overall it
is quite good!
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Inside This Book (learn more)
First Sentence:
Signal processing is concerned with the modelling, detection, identification and utilisation of patterns and structures in a signal process. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
predictor coefficient vector, stationary subprocesses, transient noise pulses, telephone line echoes, inverse channel filter, subtraction filter, blind equalisation, observation pdf, linear prediction model, most likely state sequence, hearing aid system, spectral subtraction, channel equalisation, filter coefficient vector, finite state process, input power spectrum, acoustic echo cancellation, block diagram configuration, processing distortions, spectrum subtraction, innovation signal, channel input signal, impulsive noise, subtraction factor, prior pdf
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Englewood Cliffs, Time Series Analysis, Prentice Hall, Addison Wesley, Automatic Control, Cambridge University Press, Substituting Equation, Design of Mixture Gaussian Models, Estimation of Predictor Coefficients, Estimation of Signals, Oxford University Press, Restoration of Archived Gramophone Records, San Francisco, Stanford University, University of East Anglia, Adaptive Filter Theory, Adverse Environments, Bibliography Bibliography, Hence Equation, Robust Parameter Estimation, The Algebraic Eigenvalue Problem, The Restoration of Degraded Audio Signals, Transient Noise Waveforms
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