In computer data storage, partial-response maximum-likelihood (PRML) is a method for recovering the digital data from the weak analog read-back signal...

in various ways, e.g. by Stern and Canteaut and Sendrier. Partial response maximum likelihood (PRML) is a method for converting the weak analog signal...

Alternatives include peak detection, partial-response maximum-likelihood (PRML), and extended partial-response maximum likelihood (EPRML) detection. Although advances...

maximum likelihood sequence estimation can be reduced to that of a least squares minimization. Maximum-likelihood estimation Partial-response maximum-likelihood...

entire sequence of transmitted symbols into account. This requires a maximum-likelihood sequence estimator (MLSE), which is efficiently implemented using...

density improvements enabling 36-53 sectors per track through partial-response maximum-likelihood and zone bit recording.[citation needed] The true capacity...

variables, then θ {\displaystyle \theta } can be estimated by maximum likelihood. The maximum-likelihood estimates lack a closed-form expression and must be found...

Weighted least squares Generalized least squares Linear Template Fit Maximum likelihood estimation can be performed when the distribution of the error terms...

internally use some form of run-length limited coding and partial-response maximum-likelihood.[citation needed] As of 2021[update], common uses of magnetic...

log-likelihood. Conversely, a high Fisher information indicates that the maximum is "sharp". The regularity conditions are as follows: The partial derivative...

access time (requires two-reel cassette) 1996 HP DDS3 12 GB Partial-response maximum-likelihood (PRML) reading method—no fixed thresholds 1997 IBM VTS Virtual...

being modeled; see § Maximum entropy. The parameters of a logistic regression are most commonly estimated by maximum-likelihood estimation (MLE). This...

multiplying the item response function for each item to obtain a likelihood function, the highest point of which is the maximum likelihood estimate of θ {\displaystyle...

at a maximum, the partial derivative with respect to the shape parameter equals zero, we obtain the following system of coupled maximum likelihood estimate...

(24 GB compressed) on a 125 m cartridge. DDS-3 uses PRML (Partial Response Maximum Likelihood) to minimize electronic noise for a cleaner data recording...

They proposed an iteratively reweighted least squares method for maximum likelihood estimation (MLE) of the model parameters. MLE remains popular and...

First HDD with PRML Technology (Digital Read Channel with 'partial-response maximum-likelihood' algorithm). 1991 – Areal Technology MD-2060 – 60 megabytes...

is provided by maximum likelihood estimation. Interval estimation can also be done within the AIC paradigm: it is provided by likelihood intervals. Hence...

probability of choosing to purchase is determined. Now, suppose its maximum likelihood estimator (MLE) β ^ u {\displaystyle {\hat {\beta }}_{u}} has an asymptotic...

matrices of response data. The most common approaches are types of maximum likelihood estimation, such as joint and conditional maximum likelihood estimation...

tracks simultaneously. The technique was viewed as akin to partial-response maximum-likelihood (PRML) in providing gains similar to and in addition to the...

often estimated using the maximum likelihood procedure, such an estimation being called a probit regression. Suppose a response variable Y is binary, that...

Residual sum of squares Response bias Response rate (survey) Response surface methodology Response variable Restricted maximum likelihood Restricted randomization...

parameter estimation and inference. In general, maximum likelihood estimation requires that a likelihood function be defined. This requirement then implies...

digital or 8 DDR instrumentation reels on one cassette. Also, Partial Response Maximum Likelihood (PRML) data decoding technology has its first use in Ampex's...

for each value of x, the corresponding value of y is generated as a mean response α + βx plus an additional random variable ε called the error term, equal...

time. The partial likelihood can be maximized over β to produce maximum partial likelihood estimates of the model parameters. The partial score function...

quality, the standard will employ crosstalk cancellation and partial-response maximum-likelihood (PRML) signal processing. Both companies marketed the optical...

a normal distribution, the least-squares estimators are also the maximum likelihood estimators in a linear model. However, suppose the errors are not...

for an example. In the case of logistic regression, usually fit by maximum likelihood, there are several choices of pseudo-R2. One is the generalized R2...