|Code Listing by T. R|
For a given function as a string, lower and upper bounds, number of iterations and tolerance Bisection Method is computed.
The input matrix is tested in order to know of its diagonal is dominant.
Newton's Method for Divided Differences.
The following formula is solved:
Pn(x) = f(x0) + f[x0,x1](x-x0) + f[x0,x1,x2](x-x0)(x-x1) + ... + f[x0,x1,..,xn](x-x0)(x-x1)..(x-x[n-1])
f[x0,x1] = (f(x1-f(x0))/(x1-x0)
For a given matrix of exact values and another matrix of approximated values, the following error types are computed:
- error matrix
- absolute error matrix
- relative error matrix
- absolute relative error matrix
The Fixed Point Method is applied to a given function.
Convergence conditions are as followed:
f(xa)=0 (=) xa=g(xa) => xa[n+1]=g(xn), n=0,1,..
|e(xk)| <= L^k/(1-L)*|x1-xo|
Choice for inicial...
This function will search for adaptors, such as GPIB, and return the addresses associated to each adaptor/instrument.
A string can be given at input to filter the returned addresses.
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