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by jacobolus
17 days ago
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Really? I find the part about the SVD in Axler's book extremely unhelpful, big blobs of opaque formulas and jargon with next to no explanation or context that basically require either knowing the topic fully beforehand or a huge amount of effort to parse. e.g. Axler's definition of singular values is the extremely dry and technical: > Suppose T is in L(V, W). The singular values of T are the nonnegative square roots of the eigenvalues of T†T, listed in decreasing order, each included as any times as the dimension of the corresponding eigenspace of T†T. (Using a dagger instead of an asterisk for the conjugate transpose since HN interprets and asterisk to mean italics.) If you already just proved a lot of stuff about eigenvalues, this could be a serviceable definition; at any rate it saves space. But it doesn't really explain the point. I'd recommend anyone interested in this or related topics read Trefethen & Bau (1997) Numerical Linear Algebra. |
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“You cannot read mathematics the way you read a novel.
If you zip through a page in less than an hour, you are probably going too fast.
When you encounter the phrase “as you should verify”, you should indeed do the verification, which will usually require some writing on your part.
When steps are left out, you need to supply the missing pieces.
You should ponder and internalize each definition.
For each theorem, you should seek examples to show why each hypothesis is necessary.”
It is a math studying book, not a let me chew it for you before you take it in type of a book. It requires effort, focus and missing steps are missing on purpose so you will discover them. This is the fun about studying mathematics.
Sorry you fell that way, but the book in my opinion is a masterpiece in math composition.