MATLAB

This book begins with an introduction to MATLAB, language and graphics. I found this useful (fprint instead of disp, for example). Many engineering problems are set up and solved using MATLAB functions and m-files Applications of Fourier Series, the Dynamic Response of Second-Order Systems, and problems in ordinary and partial differential equations are presented. Many of the problems are specialized (consider the forced vibration of a pile embedded in an elastic medium, for example). Overall I liked the book, it presents a brief overview of the mathematics upon which each problem is based, and the m-files are well documented. I'm using it in an Applied Mathematics class.

You can learn a lot of mathematics in this book but nothing about MATLAB. There is no good practice in this book.
A hint for the author. Try to make a CD-ROM with all examples on it. So everyone can get familiar with MATLAB and the surface. Best would be to double or triple the number of examples. (good examples in MATLAB Code)
Rethink it and I will be the first who buys the improved edition of this book otherwise you only have to change the title in :Advanced Engineering Mathematics pictures by MATLAB.
Thanks for reading.

The book organizes several complex topics in a very intuitive and logical manner, which makes it a good reference book for engineering students. A detailed section on statistics would have been helpful.

This is an excellent book for studying advanced math. Important concepts clearly explained with good matlab examples. But I was surprised to find this book titled "Engineering Math" with the miss out of some thing like probability and random variables which are of the critical importance for Electronics/Communications students.

If you are not already a superuser of MATLAB or a mathematician and want to choose one single book on MATLAB that also brings a solid math base, this is the one. The authors have chosen the subjects very well, with emphasys on the use of mathematical principles coupled with the use of the computing power offered by MATLAB.

In addition to a sound presentation of concepts - without however being extensive (or boring) on theoretical details that probably would not be relevant - this book addresses most areas of University Math (Physical Sciences undergraduate curriculum) with a wealth of good practical programming examples. I specially liked the chapters on Eigenvectors and Eigenvalues, those on Differential equations, Fourier analysis and the simple but very clear and didatic one on Discrete sytems.

In summary, although not a complete text, the subjects addressed in this book are so well presented that it can be forgiven for not covering some areas (like complex variables and calculus of variations, to name only two). There is no waste of pages in this book, but as a suggestion for future enhancement I would mention the inclusion of a chapter dedicated to exploring the graphing power available in MATLAB.

Also as a reference, for most needs you'll probably be able to start doing something productive right away after reading. Well worth its price!

This is an excellent reference book not only for matlab, also an excellent reference book for the basic concepts such as Fourier Analysis. I think any engineers who work in electric design filed must have a copy.

This book is very useful for students, scientists and researchers who work dealth with matlab program for their problems in calculations.

In recent year, there has been phenomenal growth in some methods for engineering calculation that use matlab. It's not difficult to study and very simple.

This book looks very impressive, but if you try to understand it you'll find it very mechanical. There is not much motivation behind the many pages of formulas and derivations. I'm not even sure how many people actually read those derivations becuase even in its 4th edition the book and its solution manual both have many typos (see, for example, equations 8.11 and 12.5). Even the problems are more focused on derivations than on numerical examples. This is a good cookbook if you just want to implement an algorithm or find some pointers to the original research papers. Like many other reviewers, I beleive that engineering textbooks are losing their depth and becoming more and more like instruction manuals.

I have always wondered why many people have negative opinions about books by Simon Haykin, whether it is 'Communication Systems' or 'Adaptive Filter Theory'. Particularly, this book 'Adaptive Filter Theory', in my opinion, is one of the bestbooks on this subject. As Julius Kusuma correctly mentioned, this book is indeed an "adventure ride" into the field of Adaptive Filter Theory.

I discovered this book when I was doing a class project on Self-Orthogonalizing algorithms for Adaptive Beamforming and I felt that all the relevant information that I needed was present in this book. I did'nt really feel the neccesity to refer anything outside this book.

Apart from that, this book contains everything that a graduate student needs to know about this exciting field of adaptive filters. The author assumes some background on Random Signal Theory... I'd suggest to look up Sam Shanmugan et al's, "Random Signals: Detection, Estimation and Data Analysis" before beginning to read (enjoy) this "adventure ride" on Adaptive Filters.

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.