TR2014-113
Perspective of Statistical Learning for Nonlinear Equalization in Coherent Optical Communications
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- , "Perspective of Statistical Learning for Nonlinear Equalization in Coherent Optical Communications", Signal Processing in Photonic Communications (SPPCom), DOI: 10.1364/SPPCOM.2014.ST2D.2, July 2014.BibTeX TR2014-113 PDF
- @inproceedings{Koike-Akino2014jul,
- author = {Koike-Akino, T.},
- title = {Perspective of Statistical Learning for Nonlinear Equalization in Coherent Optical Communications},
- booktitle = {Signal Processing in Photonic Communications (SPPCom)},
- year = 2014,
- month = jul,
- doi = {10.1364/SPPCOM.2014.ST2D.2},
- isbn = {978-1-55752-737-0},
- url = {https://www.merl.com/publications/TR2014-113}
- }
- , "Perspective of Statistical Learning for Nonlinear Equalization in Coherent Optical Communications", Signal Processing in Photonic Communications (SPPCom), DOI: 10.1364/SPPCOM.2014.ST2D.2, July 2014.
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Abstract:
Modern statistical learning technologies such as deep learning have a great potential to deal with linear/nonlinear fiber impairments for future coherent optical communications. We introduce various learning techniques suited for nonlinear equalizations.