Optimal precompensation for nonlinearities in longitudinal magnetic recording using dynamic programming
by Fabian Lim, Aleksandar Kavcic
International Journal of Product Development (IJPD), Vol. 5, No. 3/4, 2008

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.

Online publication date: Tue, 11-Mar-2008

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