Posts 81 - 90 of 93

다음에 대한 결과: Numerical Analysis

Finite Fourier Transform Matrix

This is the third in a series of posts on the finite Fourier transform. The Fourier matrix produces an interesting graphic and has a surprising eigenvalue distribution. ... 더 읽어보기 >>

FFT, Fast Finite Fourier Transform

This is the second in a series of three posts about the Finite Fourier Transform. This post is about the fast FFT algorithm itself. A recursive divide and conquer algorithm is implemented in an elegant MATLAB function named ffttx.... 더 읽어보기 >>

Touch-Tone Telephone Dialing 8

We all use Fourier analysis every day without even knowing it. Cell phones, disc drives, DVDs, and JPEGs all involve fast finite Fourier transforms. This post, which describes touch-tone telephone dialing, is the first of three posts about the computation and interpretation of FFTs. The posts are adapted from chapter 8 of my book, Numerical Computing with MATLAB . ... 더 읽어보기 >>

Complete Pivoting and Hadamard Matrices 1

For several years we thought Hadamard matrices showed maximum element growth for Gaussian elimination with complete pivoting. We were wrong. ... 더 읽어보기 >>

Gaussian Elimination with Partial Pivoting 1

In rare cases, Gaussian elimination with partial pivoting is unstable. But the situations are so unlikely that we continue to use the algorithm as the foundation for our matrix computations.... 더 읽어보기 >>

Floating Point Denormals, Insignificant But Controversial

Denormal floating point numbers and gradual underflow are an underappreciated feature of the IEEE floating point standard. Double precision denormals are so tiny that they are rarely numerically significant, but single precision denormals can be in the range where they affect some otherwise unremarkable computations. Historically, gradual underflow proved to be very controversial during the committee deliberations that developed the standard. ... 더 읽어보기 >>

Floating Point Numbers 5

This is the first part of a two-part series about the single- and double precision floating point numbers that MATLAB uses for almost all of its arithmetic operations. (This post is adapted from section 1.7 of my book Numerical Computing with MATLAB, published by MathWorks and SIAM.) ... 더 읽어보기 >>

Ordinary Differential Equations, Stiffness 3

Stiffness is a subtle concept that plays an important role in assessing the effectiveness of numerical methods for ordinary differential equations. (This article is adapted from section 7.9, "Stiffness", in Numerical Computing with MATLAB.) ... 더 읽어보기 >>

Ordinary Differential Equation Solvers ODE23 and ODE45 4

The functions ode23 and ode45 are the principal MATLAB and Simulink tools for solving nonstiff ordinary differential equations.... 더 읽어보기 >>

Ordinary Differential Equation Suite 4

MATLAB and Simulink have a powerful suite of routines for the numerical solution of ordinary differential equations. Today's post offers an introduction. Subsequent posts will examine several of the routines in more detail.... 더 읽어보기 >>

Posts 81 - 90 of 93