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The proposed design is evaluated in this section.
The results of audio enhancement for the music signals are analyzed and evaluated in this section.
The performances of the three newly proposed estimators are evaluated in this section.
The metrics evaluated in this section are all based on luminance information.
It should be noted that the classification performance evaluated in this section is classification accuracy at the cell level.
Similarly, by utilizing the redundancy of system dynamics, a Kalman filtering-based heuristic approach is evaluated in this section.
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We evaluate in this section Kapuer's and Kagop's efficiency against a real life scenario.
Next, we evaluate in this section a seamless adaptation of our algorithms to a dynamic environment.
Although setting an unbounded value for the number of entries k is obviously unadvisable, we additionally evaluate in this section the total overhead when the maximum list size possible is allowed for each network density.
The behavioral indicators evaluated in this research are contained in this section.
The performance characteristics of the channel estimators with optimal training sequences are evaluated in Section 6. Section 7 concludes this paper.
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