Design rational filters using numerical arithmetic operations:

x = rkfun; f1 = rkfun('step',5); f2 = rkfun('cheby',3); f2 = 1./(1 + 0.05*f2(2*x-2).^2); ezplot(f1+f2)

Partial fraction conversion and root-finding for rational functions:

r = rkfun('(x^3 - x^2 + 1)/(x^4 + 1)'); s = rkfun('cayley'); res = residue(r(s)); rts = roots(r(s)); pls = poles(r(s));

Nonlinear fitting of transfer functions and pole identification:

This slide shows the fitting of a frequency response using the RKFIT algorithm.

See this example for more details.

This slide shows the fitting of a frequency response using the RKFIT algorithm.

See this example for more details.

Parameter optimization for matrix function approximation:

Optimized poles for the approximation of the matrix exponential function.

See this example for more details.

Optimized poles for the approximation of the matrix exponential function.

See this example for more details.

The RKToolbox is downloaded and installed within seconds:

To get started, have a look at the guide and example collection.

Please contact us with any feedback or questions:

Mario Berljafa Stefan Güttel