enow.com Web Search

Search results

1. Results from the WOW.Com Content Network

2. Runge–Kutta–Fehlberg method - Wikipedia

   en.wikipedia.org/wiki/Runge–Kutta–Fehlberg...

   Download as PDF; Printable version; In other projects ... outlines a solution to solving a system of n differential equations of the form: ... L=4 L=5 1 0 25/216 16/ ...

3. Steffensen's method - Wikipedia

   en.wikipedia.org/wiki/Steffensen's_method

   % The fixed point iteration function is assumed to be input as an % inline function. % This function will calculate and return the fixed point, p, % that makes the expression f(x) = p true to within the desired % tolerance, tol. format compact % This shortens the output. format long % This prints more decimal places. for i = 1 : 1000 % get ...

4. Iteratively reweighted least squares - Wikipedia

   en.wikipedia.org/wiki/Iteratively_reweighted...

   IRLS can be used for ℓ 1 minimization and smoothed ℓ p minimization, p < 1, in compressed sensing problems. It has been proved that the algorithm has a linear rate of convergence for ℓ 1 norm and superlinear for ℓ t with t < 1, under the restricted isometry property, which is generally a sufficient condition for sparse solutions.

5. Template:L4 - Wikipedia

   en.wikipedia.org/wiki/Template:L4

   Place {} where normally would be written L 4. Optionally takes an argument nolink=yes to suppress the hyperlink, for use in headings and to avoid overlinking. Optionally takes an argument pt=yes to append the word "point" or "points". Optionally takes up to four unnamed parameters to allow the listing of a set of Lagrangian points

6. Gauss–Seidel method - Wikipedia

   en.wikipedia.org/wiki/Gauss–Seidel_method

   At any step in a Gauss-Seidel iteration, solve the first equation for in terms of , …,; then solve the second equation for in terms of just found and the remaining , …,; and continue to . Then, repeat iterations until convergence is achieved, or break if the divergence in the solutions start to diverge beyond a predefined level.

7. Linear least squares - Wikipedia

   en.wikipedia.org/wiki/Linear_least_squares

   One basic form of such a model is an ordinary least squares model. The present article concentrates on the mathematical aspects of linear least squares problems, with discussion of the formulation and interpretation of statistical regression models and statistical inferences related to these being dealt with in the articles just mentioned.

8. Plotting algorithms for the Mandelbrot set - Wikipedia

   en.wikipedia.org/wiki/Plotting_algorithms_for...

   The result of each iteration is used as the starting values for the next. The values are checked during each iteration to see whether they have reached a critical "escape" condition, or "bailout". If that condition is reached, the calculation is stopped, the pixel is drawn, and the next x, y point is examined. For some starting values, escape ...

9. Conjugate gradient method - Wikipedia

   en.wikipedia.org/wiki/Conjugate_gradient_method

   The conjugate gradient method can be derived from several different perspectives, including specialization of the conjugate direction method for optimization, and variation of the Arnoldi/Lanczos iteration for eigenvalue problems. Despite differences in their approaches, these derivations share a common topic—proving the orthogonality of the ...