What is it about?

Nonlinear equalizers play an important role in mitigating the nonlinear distortions and noises causing the errors of a detector in high-density magnetic recording (MR) systems. The efficient and effective fuzzy logic equalizer (FLE) derived by multi-objective genetic algorithm (MOGA) is among them that helps to enhance the BER performance while reducing the computational complexity and increasing the reliability.

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Why is it important?

By means of the genetic optimization and simultaneously designing fuzzy rules, the total number of fuzzy rules is significantly reduced by about 44% means reducing the system parameters which is easier meet the optimal solution, whereas the proposed FLE outperforms existing detectors by 1 to 12 dB SNR gains.


This article may be attracted the readers who interest or deal with the AI technique and evolution optimization as well as the channel equalization.

rati wongsathan
North-Chiang Mai University

Read the Original

This page is a summary of: Fuzzy Logic based Adaptive Equalizer for Nonlinear Perpendicular Magnetic Recording Channels, IET Communications, February 2019, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-com.2018.5815.
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