butools.dmap.CheckDMRAPRepresentation¶

butools.dmap.CheckDMRAPRepresentation()¶

Matlab:	r = CheckDMRAPRepresentation(H, prec)
Mathematica:	r = CheckDMRAPRepresentation[H, prec]
Python/Numpy:	r = CheckDMRAPRepresentation(H, prec)

Checks if the input matrixes define a discrete time MRAP.

All matrices H0...HK must have the same size, the dominant eigenvalue of H0 is real and less than 1, and the rowsum of H0+H1+...+HK is 1 (up to the numerical precision).

Parameters:	H : list/cell of matrices, length(K) The H0...HK matrices of the DMRAP to check
Returns:	r : bool The result of the check

Examples

For Matlab:

>>> H0 = [0.15, 0.2, 0.18; -0.23, 0.17, 0.22; 0.19, 0.15, 0.16];
>>> H1 = [0.01, 0.08, 0.16; 0.02, 0.2, 0.07; 0.02, 0.15, 0.17];
>>> H2 = [0.14, 0.07, 0.01; 0.19, 0.02, 0.34; 0.06, 0.1, 0];
>>> flag = CheckDMRAPRepresentation({H0, H1, H2});
>>> disp(flag);
     1

For Mathematica:

>>> H0 = {{0.15, 0.2, 0.18},{-0.23, 0.17, 0.22},{0.19, 0.15, 0.16}};
>>> H1 = {{0.01, 0.08, 0.16},{0.02, 0.2, 0.07},{0.02, 0.15, 0.17}};
>>> H2 = {{0.14, 0.07, 0.01},{0.19, 0.02, 0.34},{0.06, 0.1, 0}};
>>> flag = CheckDMRAPRepresentation[{H0, H1, H2}];
>>> Print[flag];
True

For Python/Numpy:

>>> H0 = ml.matrix([[0.15, 0.2, 0.18],[-0.23, 0.17, 0.22],[0.19, 0.15, 0.16]])
>>> H1 = ml.matrix([[0.01, 0.08, 0.16],[0.02, 0.2, 0.07],[0.02, 0.15, 0.17]])
>>> H2 = ml.matrix([[0.14, 0.07, 0.01],[0.19, 0.02, 0.34],[0.06, 0.1, 0]])
>>> flag = CheckDMRAPRepresentation([H0, H1, H2])
>>> print(flag)
True