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- Noise-Predictive Maximum-Likelihood (NPML) is a class of digital signal-processing methods suitable for magnetic data storage systems that operate at high linear recording densities. It is used for retrieval of data recorded on magnetic media. Data are read back by the read head, producing a weak and noisy analog signal. NPML aims at minimizing the influence of noise in the detection process. Successfully applied, it allows recording data at higher areal densities. Alternatives include peak detection, partial-response maximum-likelihood (PRML), and extended partial-response maximum likelihood (EPRML) detection. Although advances in head and media technologies historically have been the driving forces behind the increases in the areal recording density, digital signal processing and coding established themselves as cost-efficient techniques for enabling additional increases in areal density while preserving reliability. Accordingly, the deployment of sophisticated detection schemes based on the concept of noise prediction are of paramount importance in the disk drive industry. (en)
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- Noise-Predictive Maximum-Likelihood (NPML) is a class of digital signal-processing methods suitable for magnetic data storage systems that operate at high linear recording densities. It is used for retrieval of data recorded on magnetic media. (en)
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- Noise-predictive maximum-likelihood detection (en)
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