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Book Reviews of An Introduction to Signal Detection and Estimation (Springer Texts in Electrical Engineering)Book Review: Good book about detection and estimation Summary: 5 StarsThis is a textbook recommended by our instructor. The theory is useful. But I don't think the description in the book is easy for me to understand.
Book Review: Good book Summary: 5 StarsThis is indeed a good book in the field of Estimation and Detection Theory. The book is very mathematical but pretty thorough too. It assumes you know the concepts of Random Processes in depth. So a refreshing course in Random processes and probability will be a good pre-requesite before starting on this book.
Book Review: Very concise introduction to the subject Summary: 4 StarsSome say this book is hard to read. I found it quite the opposite. The book is concise, which means it takes sometime to go through each page. But the amount of information one gets is worth the effort. One downside though are the problem sets in each chapter. Most of the problems are similar and there are very few variations. Nonetheless, if you have money to spend on a sigle book on this topic this is the book to have, at least for electrical engineers and computer scientists.
Book Review: Best Book I've Seen but could be better Summary: 4 StarsPoor does a better than average job of explaining the complicated theory behind detection and estimation. He has many examples which clarifiy some complicated theorems. However I find that too many steps are skipped. Particularly in chapter II where the basis for all of the detection methods become apparent.
The book is an excellent resource for someone who wants to learn detection and estimation. However don't expect it to be your only resource. In order to understand Poor's book to its fullest you will need to find supplemental material.
Book Review: Excellent book, but not student-friendly! Summary: 4 StarsDr. Poor is a very well known authority in statistical signal processing, and in this book he offers us an excellent introductory-level presentation on a challenging and very important subject. Careful reading of this book will provide the reader with a solid theoretical background! Lots of examples and exercises to illustrate theory; nevertheless I think that some very important aspects related to practical applications should not be left as exercises (for instance M-ary hypothesis testing). I also missed some computer-based exercises; it would have been great to see the beauty of detection and estimation theory at work. If you have some familiarity with the topic you will undoubtedly enjoy this book, but if you are a student tackling with this for the first time it will be demanding reading. You will need considerable fluency in random variable calculus to get the most out of the book, as the author presents many results and derivations as "straightforward".
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