A Machine Learning Inspired Transceiver with ISI-Resilient Data Encoding: Hybrid-Ternary Coding + 2-Tap FFE + CTLE + Feature Extraction and Classification for 44.7dB Channel Loss in 7.3pJ/bit

Zhiping Wang, Mohamed Megahed, Yusang Chun, Tejasvi Anand. A Machine Learning Inspired Transceiver with ISI-Resilient Data Encoding: Hybrid-Ternary Coding + 2-Tap FFE + CTLE + Feature Extraction and Classification for 44.7dB Channel Loss in 7.3pJ/bit. In 2021 Symposium on VLSI Circuits, Kyoto, Japan, June 13-19, 2021. pages 1-2, IEEE, 2021. [doi]

Abstract

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