Fig. 6.

Schematic for the ‘backward model’ of PECAP used for the computational validation of the model accuracy and its sensitivity to noise. The two vectors σ_s and ƞ_s are initialized with pre-defined values, the backwards (grey) part of the algorithm is run to generate a simulated M_s using Eqs. (6), (4), and (3), and random Gaussian noise is added. The algorithm is then run in the normal, forward manner (black) with σ and ƞ initialized from random numbers as described previously, and the resultant final estimates of σ and ƞ are evaluated by comparing them to σ_s and ƞ_s