
Fundamentals of Statistical Signal Processing (English, Steven Kay)
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Specifications
| Publisher | Pearson |
| Language | English |
| ISBN-13 | 9780135041352 |
| ISBN-10 | 013504135X |
| Author | Steven Kay |
Product Description
Here on GlowMirror, you'll find Fundamentals of Statistical Signal Processing filed under Pearson -- everything you need to know is covered below.
About the Book
Fundamentals of Statistical Signal Processing is a carefully curated title by Steven Kay, published by Pearson.
ISBN: 9780135041352
Book Insights
What You'll Learn
- ·In-depth exploration of topics covered in Fundamentals of Statistical Signal Processing
- ·Key concepts explained with clarity and practical examples
- ·Insights valuable for anyone studying or working in Pearson
Who Should Read This
Students and professionals interested in Pearson, as well as general readers looking to expand their knowledge.
Key Highlights
- ·Brand new physical book delivered across India
- ·15-day hassle-free return policy
Customer Reviews
Excellent followup on Part I of the series
Like Part I (Estimation theory), this is not a book for anyone who is frightened by mathematics. However, if you are someone who takes the time to work through the arguments presented in this text, you will be rewarded with a profound understanding of how useful information can be gleaned from seemingly impossibly noisy signals. Recommended to anyone who wants to understand the fundamentals behind advanced communication or control systems.
My favorite text on the subject.
The text includes the perfect balance of theory and practice. I use this text more than similar texts on the subject largely because of the helpful, illustrative examples. Such examples include both very simple cases (a constant plus noise) to very complicated examples (subspace detectors, signal jamming, sonar with unknown range, frequency, amplitude). The generalized likelihood ratio and Neyman Pearson decision rule are employed in several cases. The text includes less regarding Bayesion decision rules, but these are employed less in my practice.The appendices include the proofs of several theorems. They are detailed, and great for evaluating your understanding of the material. Proofs are invaluable for stretching your thinking and only enhance your understanding of the practical aspects, too.This book works great with Vol I on Estimation Theory, which it references for maximum likelihood estimates of unknown parameters. I haven't yet checked out Vol III on Practical Algorithm development, but I bet it is as good as the first two.
Good book for discrete-time detection
As part of my research I needed the basics of detection theory. This book does the job of explaining that perfectly. Nonetheless, the continuous-time detection part is missing. If that is what you look, go with Poor's book.
Five Stars
Excellent!
Good Detection Theory book
I've used this book for one of my class. This book does a very good job at explaining concepts and it is pretty easy to follows.


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