  In this paper, a novel architecture of electro-optical neural networks based
on the time-stretch method is proposed and numerically simulated. By stretching
time-domain ultrashort pulses, multiplications of large scale weight matrices
and vectors can be implemented on light and multiple-layer of feedforward
neural network operations can be easily implemented with fiber loops. Via
simulation, the performance of a three-layer electro-optical neural network is
tested by the handwriting digit recognition task and the accuracy reaches 88%
under considerable noise.
