  In continuous-time system identification, the intersample behavior of the
input signal is known to play a crucial role in the performance of estimation
methods. One common input behavior assumption is that the spectrum of the input
is band-limited. The sinc interpolation property of these input signals yields
equivalent discrete-time representations that are non-causal. This observation,
often overlooked in the literature, is exploited in this work to study
non-parametric frequency response estimators of linear continuous-time systems.
We study the properties of non-causal least-square estimators for
continuous-time system identification, and propose a kernel-based non-causal
regularized least-squares approach for estimating the band-limited equivalent
impulse response. The proposed methods are tested via extensive numerical
simulations.
