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3 of 3 people found the following review helpful:
4.0 out of 5 stars I bought this for a class but now...., October 28, 2005
This review is from: Fundamentals of Linear State Space Systems (McGraw-Hill Series in Electrical Engineering) (Hardcover)
I constantly use this book as a reference. It has sufficient depth for a wide variety of topics and even covers the Eigensystem Realization Algorithm. Between this and the Conrad and Hitz book, I am usually able find what I need.
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1 of 1 people found the following review helpful:
4.0 out of 5 stars Pedagogically Correct, August 31, 2011
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This review is from: Fundamentals of Linear State Space Systems (McGraw-Hill Series in Electrical Engineering) (Hardcover)
It is an extremely difficult task to find a textbook that takes the reader from simple concepts studied in the first two years of a typical engineering/science program (Algebra, differential calculus, Laplace transforms, Fourier transforms, controls, etc.) and bridging the reader slowly into state-space concepts. This is the stated aim of this text: a pedagogically sound attempt at bridging the reader from simpler concepts to the state space. It does a reasonably good job at achieving it too. Most other texts don't even bother - and you can usually envision their authors arrogantly shoving their glasses up their nose as they were writing it ("I will not share my intuition!").

The first two thirds of the book fits this former description perfectly. The user is gently swept up into the state-space representation and presented with conceptual (graphical!) arguments as to its inner workings. It seemed evident to me that the resultant discussion on Lyapunov stability was extremely well motivated as a result of this graphical discussion; I have not much explored the concept myself but I can easily see how some authors would get carried away with formal mathematics and forget to again share simple intuition. As with all such endeavors, however, the more complicated concepts closer to the end of the book are often lost in overly mathematical minutiae with seemingly little effort made to bring intuition to the subject. This disappointed me since I was keenly hoping to walk away with a deep intuitive understanding of the mathematics behind the Kalman Filter (this may require a re-read of some chapters).

The book is reasonably well suited to self-study but is best used in a course whose instructor can help the student along. It is probably best left to the graduate student but could help out an undergraduate student whose professor's teaching technique is less than stellar.
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