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Using this criterion, three generic classes of objective metrics can be described: Full-reference metrics (FR): the evaluation system has access to the original media.
One of this is the amount of side information required to compute a given quality measurement; depending on this, three classes of objective metrics can be described: Full reference metrics (FR): the evaluation system has access to the original media.
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The algorithm progresses with two primary classes of objectives.
This approach leads to a specific class of objective equations and performance indices.
Due to this property these types of algorithms are potentially capable of globally optimizing any class of objective functions [2].
In [8, 9], source and relay matrices were developed to jointly optimize a broad class of objective functions.
The effectiveness and versatility of this method is illustrated on a class of objective functions for a ramp metering problem.
In this paper, we study iterative algorithms based on the conjugate function lower bound (CFLB) and minorization-maximization (MM) for a class of objective functions.
A unified framework was developed in[8, 9] to jointly optimize the source and relay matrices for a broad class of objective functions.
For a very general class of objective functions, we provide for the first time results about the quality of the solution found.
A class of objective functions, such as those found in the robust optimization package developed by Bortfeld and Unkelbach, allows for inputs in the form of probability density functions[38].
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