Probability and Statistics Review

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(More customer reviews)I found it a lucid and useful text. Could recommend it for an applied mathematician or physicist wanting to brush up on statistics.

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A developed, complete treatment of undergraduate probability andstatistics by a very well known author. The approach develops aunified theory presented with clarity and economy. Included manyexamples and applications. Appropriate for an introductoryundergraduate course in probability and statistics for students inengineering, math, the physical sciences, and computer science.(vs.Walpole/Myers, Miller/Freund, Devore, Scheaffer/McClave, Milton/Arnold)

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Mathematical Methods and Algorithms for Signal Processing Review

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(More customer reviews)This is a very unique book. It presents a range of material relevant to dsp and communications that you will not likely find together in any other book. I think the proofs and explanations are pretty clear, and the book is very readable. Although my math background is limitied to the math courses I've taken within my EE curriculum, I found the math in this book to be accessible and understandable.
What brings it down, however, is the absolutely insane number of errors and typos. The errata for the SECOND printing is 43 pages long! It's so thick that I can't even staple it together with a regular stapler. And that's just the mistakes that they've identified. Who knows how many others lurk in the text undetected.
I can understand a page or two of corrections, that is typical of most EE textbooks. And I can understand that since this is a first edition, there will be more mistakes than for a typical textbook which has been through several editions. But 43 pages worth of mistakes is unacceptable in my opinion. This material is difficult enough without mistakes in the proofs and explanations.
Without the huge errata I would have happily given this book 5 stars, but for now I give it 2.

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Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear algebra, optimization, and statistical signal processing. Interesting modern topics not available in many other signal processing books; such as the EM algorithm, blind source operation, projection on convex sets, etc., in addition to many more conventional topics such as spectrum estimation, adaptive filtering, etc. For those interested in signal processing.

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Digital Communications: Design for the Real World Review

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(More customer reviews)I'm a first year computing student taking an entry level networkings module. For the first month or so, I had quite a bit of problems understanding the concepts in the course. My problem was that I couldn't understand the lecturer, and the reference books that I borrowed never seemed to cater for new students like myself. I chanced upon this book, and it's only been a day since I've got it, but I feel that 90% of the concepts I couldn't understand have suddenly become clear to me.
I find that I can now understand the books I've been trying to read but with no success, with the basic knowledge I've gained from this book. I'd definitely recommend this book to any first/second year university student.

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Digital Communications: Design for the Real World introduces readers to the fundamentals of digital communications through an applications-driven approach.Devised specifically to serve as a first stage text for undergraduate students, this textbook + CD package relates theory to real-world products and emphasizes the design choices facing professional communications engineers, thereby bringing this exciting subject vividly to life. Students encountering communications topics for the first time, practising engineers and managers will all appreciate the stimulating and motivational treatment of the subject.

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Introduction to Spectral Analysis Review

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(More customer reviews)There are many books on spectral analysis and related topics. This book is particular suitable for the people who want to learn this topic by self-studying. The chapters are well-organized and up-to-date. If you have this book at hand, don't forget visiting the book's homepage (you can find the address in the book) and downloading some useful information, including lecture notes and MATLAB files. Those materials are really informative and helpful. I highly recommend this book for textbook in classroom or reference book for researchers.

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This book presents an introduction to spectral analysis that is designed for either course use or self-study. Clear and concise in approach, it develops a firm understanding of tools and techniques as well as a solid background for performing research. Topics covered include nonparametric spectrum analysis (both periodogram-based approaches and filter- bank approaches), parametric spectral analysis using rational spectral models (AR, MA, and ARMA models), parametric method for line spectra, and spatial (array) signal processing. Analytical and Matlab-based computer exercises are included to develop both analytical skills and hands-on experience.

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Time Frequency Analysis: Theory and Applications Review

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(More customer reviews)This book is written clearly and well by a leading researcher in the area of time-frequency analysis. The main weakness, and the reason I've knocked off one star, is that the book deals exclusively with continuous-time representations. If you are specifically interested in discrete-time implementation of time-frequency representations, then this book may not be for you.

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Featuring traditional coverage as well as newresearch results that, until now, have been scattered throughout theprofessional literature, this book brings together—in simple language—thebasic ideas and methods that have been developed to study naturaland man-made signals whose frequency content changes with time—e.g.,speech, sonar and radar, optical images, mechanical vibrations, acousticsignals, biological/biomedical and geophysical signals. Coverstime analysis, frequency analysis, and scale analysis; time-bandwidthrelations; instantaneous frequency; densities and local quantities;the short time Fourier Transform; time-frequency analysis; the Wignerrepresentation; time-frequency representations; computation methods;the synthesis problem; spatial-spatial/frequency representations;time-scale representations; operators; general joint representations;stochastic signals; and higher order time-frequency distributions.Illustrates each concept with examples and shows how the methods havebeen extended to other variables, such as scale. Forengineers, acoustic scientists, medical scientists and developers,mathematicians, physicists, and mangers working in the fields of acoustics,sonar, radar, image processing, biomedical devices, communication.

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Adaptive Filter Theory (4th Edition) Review

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(More customer reviews)Despite the commonly negative opinion against Simon Haykin's book, I find this book to be a very fun reading. It starts off with a very brief review of DSP (more useful just for getting familiar with the notation, really), properties of random processes, and a small section on linear algebra in the middle of the book.
The rest of the book can be viewed as a story of how different approaches and algorithms were developed, and is a little difficult to use as reference due to its lack of structure and over-dependency on the previous chapters, both for technical content and notation.
But there's a lot of hidden treasures within this book that should have been more emphasized. For example, Mold's theorem that states that any discrete stationary process can be decomposed into a deterministic component and a random component, which are uncorrelated to each other. I'm sorry, but a reference to a proof in another book is not enough to really motivate me. This is a very fundamental theorem if you're interested in stochastic signal processing. Sure, you don't cover the Fundamental Theorem of Calculus in your very first calculus class, but then again this is supposed to be a fairly advanced book.
So if you're interested in learning certain things quickly, this is NOT the book to get. Consider Munson Hayes' book instead. Save this one when you feel like investing a little time to hear Haykin's story on stochastic signal processing.

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Adaptive Filter Theory, 4e, is ideal for courses in Adaptive Filters.

Haykin examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons. In its fourth edition, this highly successful book has been updated and refined to stay current with the field and develop concepts in as unified and accessible a manner as possible.

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Fast Fourier Transform and Its Applications Review

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(More customer reviews)Fourier transforms used to scare me. I got brain-lock, and couldn't even use them effectively in a package like Matlab or IDL. I got lost in integrals and delta functions and found myself rapidly sinking into mathematical quicksand. Evoking qliphotic demons from within a pentagram of power would have been simpler and less arcane.
Then along came Brigham. Although his book had all the gnarly math of any other Fourier transform explanation I had ever seen, he also drew diagrams--diagrams which allowed me to "get" what the language of mathematics had so clearly expressed. All of a sudden the integrals were tamed. I wasn't in quicksand, just a damp sidewalk at Adventureland, waiting for the Jungle Cruise.
And that was just the first couple of chapters! Brigham quickly moved into transform theory, applying the Fourier integral to convolution and correlation. Then into sampled waveforms and the discrete Fourier transform and its applications.
Finally, he presented the Fast Fourier Transform. Once again, he clarifies without obfuscating. I found the FFT moving from the hyper-arcane to the land of "Well, duh!" (Beware: The actual FFT code included is not particularly efficient. Find source code for implementation *elsewhere*.) He extends the FFT to convolution and correlation, as well as to two dimensions. He doesn't skimp on applications, either. He clarifies interferometry, time-difference-of-arrival, power spectrum analysis, and beamforming.
If you're not a signal processing wonk already, read this book. You may find it a powerful cure for DSP-phobia.

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The Fast Fourier Transform (FFT) is a mathematical method widely used in signal processing. This book focuses on the application of the FFT in a variety of areas: Biomedical engineering, mechanical analysis, analysis of stock market data, geophysical analysis, and the conventional radar communications field.

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