numerical_analysis_9th 数值分析第九版，经典算法书

madio

This book was written for a sequence of courses on the theory and application of numerical
approximation techniques. It is designed primarily for junior-level mathematics, science,
and engineering majors who have completed at least the standard college calculus sequence.
Familiarity with the fundamentals of linear algebra and differential equations is useful, but
there is sufficient introductory material on these topics so that courses in these subjects are
not needed as prerequisites.
Previous editions of Numerical Analysis have been used in a wide variety of situations.
In some cases, the mathematical analysis underlying the development of approximation
techniques was given more emphasis than the methods; in others, the emphasis was reversed.
The book has been used as a core reference for beginning graduate level courses
in engineering and computer science programs and in first-year courses in introductory
analysis offered at international universities. We have adapted the book to fit these diverse
users without compromising our original purpose:
To introduce modern approximation techniques; to explain how, why, and when they
can be expected to work; and to provide a foundation for further study of numerical
analysis and scientific computing.
The book contains sufficient material for at least a full year of study, but we expect many
people to use it for only a single-term course. In such a single-term course, students learn
to identify the types of problems that require numerical techniques for their solution and
see examples of the error propagation that can occur when numerical methods are applied.
They accurately approximate the solution of problems that cannot be solved exactly and
learn typical techniques for estimating error bounds for the approximations. The remainder
of the text then serves as a reference for methods not considered in the course. Either the
full-year or single-course treatment is consistent with the philosophy of the text.
Virtually every concept in the text is illustrated by example, and this edition contains
more than 2600 class-tested exercises ranging from elementary applications of methods
and algorithms to generalizations and extensions of the theory. In addition, the exercise
sets include numerous applied problems from diverse areas of engineering as well as from
the physical, computer, biological, economic, and social sciences. The chosen applications
clearly and concisely demonstrate how numerical techniques can be, and often must be,
applied in real-life situations.
A number of software packages, known as Computer Algebra Systems (CAS), have
been developed to produce symbolic mathematical computations. Maple®, Mathematica®,
and MATLAB® are predominant among these in the academic environment, and versions
of these software packages are available for most common computer systems. In addition,
Sage, a free open source system, is now available. This system was developed primarily