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Conferences > OECC > 2021 > T2B > T2B.4

FPGA-based Implementation of Artificial Neural Network for Nonlinear Signal-to-Noise Ratio Estimation

Lei Liu, Xiaomin Liu, Zhiqun Zhai, Yiwen Wu, Hexun Jiang, Lilin Yi, Weisheng Hu, and Qunbi Zhuge

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Abstract

We propose a FPGA-based artificial neural network (ANN) architecture with flexible degree of parallelism (DOP) for nonlinear signal-to-noise ratio (SNR) estimation. Considering the trade-off between resource usage and computational speed, the architecture shows flexibility and efficiency of resources allocation in the FPGA design.

© 2021 The Author(s)

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