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...

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

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

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

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

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...

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

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

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

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

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

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

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

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

(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...

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...

likelihood function and it is closely related to the Akaike information criterion (AIC). When fitting models, it is possible to increase the maximum likelihood...

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...

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...

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

binomial distributions), standardized least-squares estimates and maximum-likelihood estimates are identical. The method of least squares can also be derived...

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...

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

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

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

{\displaystyle \ln(P)} since in the context of maximum likelihood estimation the aim is to locate the maximum of the likelihood function without concern for its absolute...

the maximum-likelihood estimator is: e − 2 λ − e λ ( 1 / e 2 − 1 ) . {\displaystyle e^{-2\lambda }-e^{\lambda (1/e^{2}-1)}.\,} The bias of maximum-likelihood...