Introduction to numerical analysis

Error

Functions and Calculus

Interpolation & numerical differentiation

Interpolation

Fitting

Numerical integration

Solving Equations

Numerical linear algebra

Notes: 用高斯消元法求解时,比较计算后和计算前的主对角元,比值越小、解的精度就少多少(?) (Using double precision floating point number) 系数矩阵条件数在百亿量级(1e10)时, 解的精度大概只有1e-3或1e-4。——陈璞

Nonlinear equations

Newton method

Merit function for solving nonlinear equations is a scalar-valued function that indicates whether a new iterate is better or worse than the current iterate, in the sense of making progress toward a root. Merit functions are often obtained by combining the components of the vector field in some way, e.g. the sum of squares; all of which have some drawbacks.

Line search and trust-region techniques play an equally important role in optimization, but one can argue that trust-region algorithms have certain theoretical advantages in solving nonlinear equations.

Ordinary differential equations

Optimization

Optimization:

References

  • Golub and Van Loan, 1983, 2013. Matrix Computations.
  • Dennis and Schnabel, 1983, 1996. Numerical Methods for Unconstrained Optimization and Nonlinear Equations.
  • Nocedal and Wright, 1999, 2006. Numerical Optimization.

🏷 Category=Computation