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Conferences > OFC > 2022 > W2A > W2A.26

Computationally-Efficient Sparsely-Connected Multi-Output Neural Networks for IM/DD System Equalization

Zhaopeng Xu, Shuangyu Dong, Honglin Ji, Jonathan H. Manton, and William Shieh

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Abstract

Low-complexity sparsely-connected multi-output neural networks are proposed for equalization in a 50-Gb/s 25-km PAM4 IM/DD system. Compared with traditional fully-connected single-output counterparts, a gross complexity reduction of 60.4%/56.7% can be achieved with 2-layer FNN/C-FNN architecture.

© 2022 The Author(s)

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