Leon Q. Brin’s "Tea Time Numerical Analysis" #numerical-methods #ebook home page (CC-BY-SA). Very good coverage, including historical documents. Starts a bit more basic than the other alternatives. Covers root finding (bisection, fixed-point iteration, Steffensen’s method for accelerating it, Newton’s method, synthetic division, Müller’s method), interpolation (Lagrange polynomials, Neville’s method, Newton polynomials, divided differences, Bèzier curves, splines), quadrature, ordinary differential equations (Taylor methods, #Runge-Kutta, adaptive Runge-Kutta). Includes proofs and error bounds, with more of a mathematical orientation than the alternatives. #math 375 pp.
on 02021-12-05another #numerical-methods #ebook, this one using Python, including floating-point error, bisection, regula falsi, Newton’s method, the method of secants, numerical optimization including Simpson’s rule, LU factorization, QR factorization, least-squares curve fitting, eigenvalue computation, ODE integration (the midpoint method, #Runge-Kutta, backwards Euler), PDEs (the heat equation and the wave equation), Vandermonde interpolation, Lagrange interpolation, and Chebyshev points #math
on 02021-12-05#numerical-methods #ebook and online courseware; covers least squares, numerical integration of ODE with #Runge-Kutta and #leapfrog-integration; ODEs with boundary conditions; PDEs including elliptic, parabolic, and hyperbolic; successive over-relaxation (SOR); fluid dynamics; Navier-Stokes; Boltzmann’s equation; neutron transport; Monte Carlo techniques, including for radiation transport; etc. #math
on 02021-12-05