for arbitrary input excitations is presented.

Multisine input signal
----------------------

We consider multisine input signals of the form $$\label{inputmultisine}
u(t)=\alpha_0+\sum_{l=1}^{m_u} \alpha_{l} \cos(\omega_l t + \psi_l),$$ where $m_u,\{\alpha_l\}_{l=0}^{m_u},\{\omega_l\}_{l=0}^{m_u}$ and $\{\psi_l\}_{l=0}^{m_u}$ are input parameters. The frequencies $\omega_l$ are assumed to be positive and distinct, and without loss of generality we assume that the weights $\alpha_l$ are positive as well. It is well known that the output in stationary regime of an asymptotically stable LTI filter $H(s)$ when $u(t)$ is applied is also a multisine, given by $$\label{eval3}
y(t)=H(0)\alpha_0+\sum_{l=1}^{m_u} \alpha_l|H(i\omega_l)| \cos(\omega_l t + \psi_l+\angle H(i\omega_l)).$$ This property of LTI systems provides a natural way to obtain exact values for the signal evaluations in and , and it is of low computational cost, since the prefiltering is directly obtained by evaluating with the corresponding filter. Another advantage of this approach is that it extends naturally to non-uniformly sampled data. For such type of sampling, the proposed method is not as computationally intensive as the standard SRIVC method, since the algorithm only obtains approximations of the filtered output $p^i A_j^{-1}(p)y(t_k), i=0,\dots,n$, instead of computing approximations of the filtered values of both $u(t_k)$ and $y(t_k)$. The filtered output computations can be carried out by, e.g., an 