Optimal precompensation for nonlinearities in longitudinal magnetic recording using dynamic programming

Fabian Lim and Aleksandar Kavcic

International Journal of Product Development, 2008, vol. 5, issue 3/4, 410-429

Abstract: We propose a dynamic programming approach to compute optimal precompensation that minimises the Mean Squared Error (MSE) between a nonlinear read-back signal and a linear one. This is done by assuming that the nonlinear read-back signal can be represented by a known finite state machine model. We show how to use finite and infinite horizon dynamic programming techniques to minimise the MSE cost function. Suboptimal techniques are studied, and performance comparisons are performed using computer simulations.

Keywords: dynamic programming; NLTS; magnetic recording; partial erasure; precompensation; finite state machine models; simulation; nonlinearities. (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpdev:v:5:y:2008:i:3/4:p:410-429

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