Carnegie Mellon University

Data Storage Systems Center

College of Engineering

ML Channel for Nonlinear Read Back in HDD

Objective: Understanding the Impact of Nonlinearity in Read Back for ML Channel.
Feature: Explore ML channel capability for various types of read back nonlinearity.

A ML data detection channel is likely to be capable of performing data recovery in read back with severe nonlinearity. If true, it will open up a new design space for future read heads that could lead to significant ADC gain. In this study, we systematically build quantitative and qualitative understanding of the ML channel’s ability in dealing with nonlinearity in read back voltage waveforms.

ML Impact on Reader Design01_HAMR_Holistic_Modeling.png

 

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