Analysis of Noise Spectral Density for Phenomenological Models of Hysteresis

A statistical technique based on Monte Carlo simulations is developed to compute the spectral densities of the output variable in phenomenological models of hysteresis. The input signal is described by an Ornstein-Uhlenbeck process and the magnetization is computed by using various hysteresis models: the Energetic, Jiles-Atherton, and Preisach models. General qualitative features of these spectral densities are examined and their dependence on various parameters is discussed. For values of the diffusion coefficient near and smaller than the coercive field, the output spectra deviate significantly from the Lorentzian shape, which is characteristic of the input process. The intrinsic differences between the transcendental, differential, and integral modeling of hysteresis yield significantly different spectra at low frequency region, which reflect the long-time correlation behavior.