We have demonstrated the applicability of
neural-network-based systems to the problem
of reducing the effects of signal distortion,
and shown that such a system has the potential
to reduce the bit-error-rate in the digitized
version of the analogue electrical signal
derived from an optical data stream by a
substantial margin over existing techniques

Boscolo, S.

Davey, N.

Hunt, S.

Shafarenko, A.

Sun, Yi

Turitsyn, S.K.

English

A Simple Yet Accurate Neural Branch Predictor,

Application of Electronic Equalization and Error Correction in Lightwave Systems,

Electrical equalization for advanced optical communication systems,

Electronic equalization of transmission impairments

Evidence-based Static Branch Prediction using Machine Learning,

NetLab: Algorithms for Pattern Recognition

Neural Methods for Dynamic Branch Prediction,

Performance of single-mode fiber links using electronic feedforward and decision feedback equalizers,

Using Simple Neural Networks to Correct Errors in Optical Data Transmission.