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Detection of Signals in Noise, Second Edition [Hardcover]

Robert N. McDonough (Author), A. D. Whalen (Author)
3.0 out of 5 stars  See all reviews (8 customer reviews)

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Book Description

May 1, 1995 0127448527 978-0127448527 2
The Second Edition is an updated revision to the authors highly successful and widely used introduction to the principles and application of the statistical theory of signal detection. This book emphasizes those theories that have been found to be particularly useful in practice including principles applied to detection problems encountered in digital communications, radar, and sonar.

Detection processing based upon the fast Fourier transform

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Product Details

  • Hardcover: 495 pages
  • Publisher: Academic Press; 2 edition (May 1, 1995)
  • Language: English
  • ISBN-10: 0127448527
  • ISBN-13: 978-0127448527
  • Product Dimensions: 9.2 x 6.1 x 1 inches
  • Shipping Weight: 1.8 pounds (View shipping rates and policies)
  • Average Customer Review: 3.0 out of 5 stars  See all reviews (8 customer reviews)
  • Amazon Best Sellers Rank: #968,679 in Books (See Top 100 in Books)

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8 Reviews
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7 of 7 people found the following review helpful:
5.0 out of 5 stars An Advanced Book on Detection Theory, March 25, 2003
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Kevin (Columbia, MD, United States) - See all my reviews
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This review is from: Detection of Signals in Noise, Second Edition (Hardcover)
This is perhaps the best book available for advanced detection theory. The probabalistic underpinnings are discussed at length. A lot of the other reviews complain about the mathematical difficulty of this text; however, it is an advanced text. Not all texts are required to be accessible to beginners in the subject. If you want to become an expert in detection theory, this is the next step after your introductory course(s). To really get there, you need to have experience in the applications as well.

If you don't have some background in detection theory or at least hypothesis testing, then in my estimation this is probably not the book for you. On the other hand if the myriad texts available are beginning to appear to be a little bit weak on the probability/statistics analysis of signals, then this is the book for you.

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6 of 6 people found the following review helpful:
5.0 out of 5 stars The Book on Advanced Detection Theory, September 24, 2003
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Richard P. Hodges (Waterford, CT. USA) - See all my reviews
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This review is from: Detection of Signals in Noise, Second Edition (Hardcover)
As far as I am concerned this is simply the best book for advanced detection theory. Notice the word "advanced", this book is not for the beginner. It is an updated version of Whalen's first edition, which I have kept close at hand for most of my career. Whereas most texts available are weak on the statistical analysis of signals, this book is strong. I would be surprised if anyone who considered himself an expert on detection theory did not have a copy. If it has a weakness it is in showing the direct connections to applications.
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8 of 9 people found the following review helpful:
5.0 out of 5 stars It's got a good beat and you can dance to it., August 19, 1998
A Moby Dickian tour de force through the noise that is Mother Nature! If you want to understand signal detection and solve real-world problems, this is the book to buy.
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Inside This Book (learn more)
First Sentence:
Engineering is often regarded as a discipline which deals in precision. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
detecting sine waves, unknown carrier phase, elementary outcomes, binary communication system, inverse kernel, quadratic detector, squared envelope, abstract experiment, absorbing constants, real envelope, complex envelope, optimum receiver, whitening filter, covariance kernel, fading signals, false alarm probability, analytic signal, binary problem, correlation receiver, detection statistic, narrowband signals, linear detector, incomplete beta function, noncentrality parameter, signal envelope
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Bell Syst, Detection of Known Signals, Gaussian Derived Processes, Marcum Q-function, Fourier Series Representation
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