The Symmetric Eigenvalue Problem (Classics in Applied Mathematics, Series Number 20) by Beresford N. Parlett (PDF)

Description

According to Parlett, ‘Vibrations are everywhere, and so too are the eigenvalues associated with them. As mathematical models invade more and more disciplines, we can anticipate a demand for eigenvalue calculations in an ever richer variety of contexts.’ Anyone who performs these calculations will welcome the reprinting of Parlett’s book (originally published in 1980). In this unabridged, amended version, Parlett covers aspects of the problem that are not easily found elsewhere. The chapter titles convey the scope of the material succinctly. The aim of the book is to present mathematical knowledge that is needed in order to understand the art of computing eigenvalues of real symmetric matrices, either all of them or only a few. The author explains why the selected information really matters and he is not shy about making judgments. The commentary is lively but the proofs are terse.

User’s Reviews

Editorial Reviews: Book Description Presents the mathematical knowledge needed in order to understand the art of computing eigenvalues of real symmetric matrices,

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐Eigenvalue hunting is a challenging, nontrivial task that plays a role in an ever widening range of technical areas. Parlett’s book is a must have reference for anyone engaged in eigen-analysis.

⭐A droll explication of techniques that can be applied to understand some of the most important engineering problems: those dealing with vibrations, buckling, and earthquake resistance. While containing substantial theory, this is an applied mathematics text that reads as if you are eavesdropping on the author talking out loud to himself. What sets it off from the crowd of math books are the inside references to Parlett’s friends in the business, and the dry wit. It contains NO CODE, yet discusses algorithms in detail, describing where they are good, and where they flop. The reader must pay attention, however, and work through some of the exercises with a calculator (a spreadsheet is handier, in my view). If you are looking for eigenvalues, this text is a necessary part of your toolkit.

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