In computer data storage, partial-response maximum-likelihood (PRML) is a method for recovering the digital data from the weak analog read-back signal...
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Decoding methods (redirect from Maximum likelihood decoding)
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...
12 KB (1,867 words) - 07:02, 11 January 2024
Alternatives include peak detection, partial-response maximum-likelihood (PRML), and extended partial-response maximum likelihood (EPRML) detection. Although advances...
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maximum likelihood sequence estimation can be reduced to that of a least squares minimization. Maximum-likelihood estimation Partial-response maximum-likelihood...
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density improvements enabling 36-53 sectors per track through partial-response maximum-likelihood and zone bit recording.[citation needed] The true capacity...
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internally use some form of run-length limited coding and partial-response maximum-likelihood.[citation needed] As of 2021[update], common uses of magnetic...
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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...
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Fisher information (section In terms of likelihood)
similar log-likelihood. Conversely, high Fisher information indicates that the maximum is sharp. The regularity conditions are as follows: The partial derivative...
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Generalized linear model (section Maximum likelihood)
They proposed an iteratively reweighted least squares method for maximum likelihood estimation (MLE) of the model parameters. MLE remains popular and...
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variables, then θ {\displaystyle \theta } can be estimated by maximum likelihood. The maximum-likelihood estimates lack a closed-form expression and must be found...
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Beta distribution (section Maximum likelihood)
at a maximum, the partial derivative with respect to the shape parameter equals zero, we obtain the following system of coupled maximum likelihood estimate...
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Continuous phase modulation (redirect from Partial response channel)
entire sequence of transmitted symbols into account. This requires a maximum-likelihood sequence estimator (MLSE), which is efficiently implemented using...
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First HDD with PRML Technology (Digital Read Channel with 'partial-response maximum-likelihood' algorithm). 1991 – Areal Technology MD-2060 – 60 megabytes...
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Weighted least squares Generalized least squares Linear Template Fit Maximum likelihood estimation can be performed when the distribution of the error terms...
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being modeled; see § Maximum entropy. The parameters of a logistic regression are most commonly estimated by maximum-likelihood estimation (MLE). This...
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quality, the standard will employ crosstalk cancellation and partial-response maximum-likelihood (PRML) signal processing. Both companies will market the...
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Probit model (section Maximum likelihood estimation)
often estimated using the maximum likelihood procedure, such an estimation being called a probit regression. Suppose a response variable Y is binary, that...
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(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...
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likelihood function and it is closely related to the Akaike information criterion (AIC). When fitting models, it is possible to increase the maximum likelihood...
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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...
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function can be maximized over β to produce maximum partial likelihood estimates of the model parameters. The partial score function is ℓ ′ ( β ) = ∑ i : C...
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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...
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Coefficient of determination (redirect from Partial R-square)
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...
45 KB (6,193 words) - 13:21, 19 August 2024
binomial distributions), standardized least-squares estimates and maximum-likelihood estimates are identical. The method of least squares can also be derived...
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In probability theory and statistics, partial correlation measures the degree of association between two random variables, with the effect of a set of...
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is provided by maximum likelihood estimation. Interval estimation can also be done within the AIC paradigm: it is provided by likelihood intervals. Hence...
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parameter estimation and inference. In general, maximum likelihood estimation requires that a likelihood function be defined. This requirement then implies...
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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...
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{\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...
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Confidence interval (section Likelihood theory)
generalization of the maximum likelihood approach. There are corresponding generalizations of the results of maximum likelihood theory that allow confidence...
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