  Reservoir computing is an information processing technique, derived from the
theory of neural networks, which is easy to implement in hardware. Several
reservoir computer hardware implementations have been realized recently with
performance comparable to digital implementations, which demonstrated the
potential of reservoir computing for ultrahigh bandwidth signal processing
tasks. In all these implementations however the signal pre-processing necessary
to efficiently address the reservoir was performed digitally. Here we show how
this digital pre-processing can be replaced by an analog input layer. We study
both numerically and experimentally to what extent the pre-processing can be
replaced by a modulation of the input signal by either a single sine-wave or by
a sum of two sine functions, since harmonic oscillations are particularly easy
to generate in hardware. We find that the modulation by a single sine gives
performance worse than state of the art. On the other hand, on many -but not
all- tasks, the modulation by two sines gives performances comparable to the
state of the art. The present work thus represents an important step towards
fully autonomous, ultrahigh bandwidth analog reservoir computers.
