  Nonlinearity is a crucial characteristic for implementing hardware security
primitives or neuromorphic computing systems. The main feature of all
memristive devices is this nonlinear behavior observed in their current-voltage
characteristics. To comprehend the nonlinear behavior, we have to understand
the coexistence of resistive, capacitive, and inertia (virtual inductive)
effects in these devices. These effects originate from corresponding physical
and chemical processes in memristive devices. A physics-inspired compact model
is employed to model and simulate interface-type RRAMs such as
Au/BiFeO$_{3}$/Pt/Ti, Au/Nb$_{\rm x}$O$_{\rm y}$/Al$_{2}$O$_{3}$/Nb, while
accounting for the modeling of capacitive and inertia effects. The simulated
current-voltage characteristics align well with experimental data and
accurately capture the non-zero crossing hysteresis generated by capacitive and
inductive effects. This study examines the response of two devices to
increasing frequencies, revealing a shift in their nonlinear behavior
characterized by a reduced hysteresis range and increased chaotic behavior, as
observed through internal state attractors. Fourier series analysis utilizing a
sinusoidal input voltage of varying amplitudes and frequencies indicates
harmonics or frequency components that considerably influence the functioning
of RRAMs. Moreover, we propose and demonstrate the use of the frequency spectra
as one of the fingerprints for memristive devices.
