This is an outstanding introduction to Matlab, and the examples work equally well with the GNU free version. Hats off to Amazon and the publisher for delivering this fine and current text at under $40 US new including web resources.

There are numerous, out of date, but well written "specialty" Matlab books-- Matlab for scientists, Matlab for Chemists, Matlab for Physicists, Matlab for Engineers, Matlab for Neurologists... etc. These almost all go for between $80 and $200+ US! This book is hands down FAR BETTER as both an intro and a reference. You HAVE to run the examples as the solutions are not always given, but Matlab itself will let you know how you did if you got the code right.

For a very recent book, the code runs quite well, I'd put it at about 95%+. Many books like this, when recently published, are rushed to press and the code is, well, frankly, garbage! The neat thing is that since this is a third edition, the code has been vetted many times and is far more bulletproof than the normal up to date, current version text.

How does it compare to the Matlab documentation? No contest! The official documentation gives volumes (libraries) on functions, etc. but very few good, basic examples of best practices. This author really knows her stuff, and will save you a ton on bugs, even if you just get this as a reference. Granted, the focus of the examples is Engineering, but I also work in medical and robotics EE and DSLs, and the examples are easily transportable to any other area. It is pretty clear that although the author publishes in advanced Engineering, she also teaches undergrads, so the book is kept intelligible without the usual "show off" style that makes many texts tough to learn from. This book is ideal for autodidacts and self study as well as reference due to that pedagogy.

Given the maturity of Matlab libraries now, there are tons of templates for every possible application imaginable, from macros and plug ins to complete APIs! So you really need best programming and problem solving practices, not 800 pages of examples for $200 using your own field's parameters and quantities-- let your plug ins and libraries do that (many of them are free now, especially with the GNU version of Matlab). I guess what I'm saying is, if you're considering spending $100 plus on a specialty Matlab book vs this-- get this instead, then use the web to find your perfect app/ specialty plug in! With this as a foundation, you don't have to get "Matlab for Signal Processing" because the plug ins are much more specific than even that "specialty" book, and give you a choice of analog, digital, time vs. frequency, RF specific, etc., for example.

Highly recommended. Does not require previous programming knowledge, but a foundation understanding (basic undergrad) of how math relates to computing (ie. linear algebraic conversion of formulas to numeric methods via vectors and matrices) is helpful. Best brush up would be in what is now called "discrete" math-- or all the numeric methods that have now been removed from the HS curriculum. Even knowing one very simple (even scripting) language also will help if you're tackling this right out of HS. You don't have to be a Java, C++, Python etc. jock to get this, and even php or javascript will help. If you've used an IDE or SDK before to debug any program, the Matlab interface will be a natural, and seem very intuitive. Plug ins are now available for popular languages that mimic Matlab, like numPy for Python, and are often used for building apps around the calculations or results, so this text also will help even if you intend to move on to languages with huge libraries like Java or Python.

Even if you go into research with a heavier emphasis on stats, for example, you'll probably prefer a language like R, but this text, and Matlab, will help with special functions and the interface even if you do end up doing most of your work in R. The most recent versions of both R and Matlab share (to put it politically) a lot of features, so you won't go wrong with this text even if you're combining with studying or using R. When you move from research to applications, design and engineering move quickly to Matlab.

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