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Exact(5)

which maximizes the criterion (13).

where is the mean and the sample size of class, ; is the maximum likelihood estimates of the covariances matrices of classes ; represents the new space that maximizes the criterion.

As a choice of λ is required to produce a unique RMIP and thereby ensure meaningful comparison with LLARRMA, we select λ to produce the stiffest possible competition: as the value that maximizes the criterion used for comparing methods.

In doing this, Fisher's discriminant function is defined as the linear function w T x that maximizes the criterion (6) J (w ) = w T S B w w T S W w, where w, S B, and S W denote weights, between and within variances of two groups, respectively.

We add such variable Z = (Z 1,…, Z n ) T not included in S to the set S, which maximizes the criterion (20) max ⁡ ⁡ r LWS Y, Z − γ ∑ k ∈ S r ~ ∗ X k, Z, over all variables not included in S and over all values of γ ≥ 0. Other variables are included step by step to S, until S contains a fixed number of variables, determined before the computations.

Similar(55)

The task of maximizing the criterion function is transformed into the problem of determining an eigenvalue of a certain matrix via a differential equation approach.

Thus, for some choice of K, we estimate π and ρ by maximizing the criterion in (4), which only involves (y1,..., y G ).

First, it is defined a criteria (e.g.: availability or cost) and objectives which can be minimize or maximize the criteria previously defined.

At this stage, the user of the tool must define the criteria function (e.g. availability or cost) and the objective which be minimized or maximized the criteria previously defined.

To overcome these problems, we use multiple hypotheses of the initial target position and vertical orientation and find the best solution that maximizes the MAP criterion.

We attempt to solve the aforementioned two problems, i.e., the initial target altitude estimation and target elevation movement direction (ascending or descending), by making multiple hypotheses of the initial target position and vertical orientation and find the best solution that maximizes the MAP criterion.

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