  Nowadays, Information Photonics is extensively studied and sees applications
in many fields. The interest in this breakthrough technology is mainly
stimulated by the possibility of achieving real-time data processing for
high-bandwidth applications, still implemented through small-footprint devices
that would allow for breaking the limit imposed by Moore's law. One potential
breakthrough implementation of information photonics is via integrated photonic
circuits. Within this approach, the most suitable computational scheme is
achieved by integrated photonic neural networks. In this chapter, we provide a
review of one possible way to implement a neural network by using silicon
photonics. Specifically, we review the work we performed at the Nanoscience
Laboratory of the University of Trento. We present methodologies, results, and
future challenges about a delayed complex perceptron for fast data processing,
a microring resonator exploiting nonlinear dynamics for a reservoir computing
approach, and a microring resonator with the addition of a feedback delay loop
for time series processing.
