The treatment of hysteresis in numerical simulations represents major issues as large computational times and significant memory space allocations are required. The memory management of the Jiles-Atherton model is simple, but its integration requires relatively fine temporal discretization to achieve convergence. Oppositely, the Preisach model gives satisfactory results with a coarser temporal grid but requires vast memory space and complex management. The Derivative Static Hysteresis Model (DSHM) is an alternative solution for improved performances. The hysteresis law is considered in a generalized input vector space. An interpolation matrix is constructed with the columns and rows denoting the discrete values of H and B and whose terms stand for the dB/dH slope at the corresponding point. Up to now, the filling step of the DSHM matrix has always been through experimental first-order reversal curves, but getting such experimental data is always complex. In this study, we propose to fill the DSHM matrix alternatively. We use simulated first-order reversal curves obtained from the Jiles-Atherton or the Preisach model, which have been identified using limited experimental data (the first magnetization curve and the major hysteresis cycle).