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Effects of CD and first order PMD on the shape of the constellation diagrams of DQPSK systems are presented, and by quantifying variations in the constellation diagrams, a figure of merit is obtained which can be used for computing the amount of dispersion.
We propose a technique using artificial neural networks to simultaneously identify fiber nonlinearity, OSNR, CD, and PMD from eye-diagram and eye-histogram parameters. A correlation coefficient of 0.97 is obtained for a set of testing data.
A technique using artificial neural networks to simultaneously identify OSNR, CD, and PMD from eye-diagram parameters is demonstrated both via simulation and experimentally in 40 Gb/s OOK and DPSK systems. A correlation coefficient of 0.99 is obtained for the testing data of both systems.
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