As digital data grows explosively year after year, magnetic tape devices, with their high reliability and long-term storage capacity, are widely used for backup and archiving. Magnetic tape devices with larger capacity are required, and it is necessary to improve track density. We have previously constructed a simulator that considers inter-track interference due to narrower tracks in barium ferrite (BaFe) magnetic tape drives and evaluated its performance. In this study, we develop a simulator which more accurately models the experimental data, considering amplitude fluctuations caused by the problem of poor tape running, and discuss the usefulness of a neural network equalizer to reduce the effects of amplitude fluctuations. As a result, we show that applying the neural network equalizer is useful in reducing the impact of amplitude fluctuations caused by the problem of poor tape running.
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