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The proposed method is compared with two conventional first level adaptation and model reference adaptive control techniques.
In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems.
In comparison with traditional approaches, the adaptive schemes provide a better performance over non-adaptive approaches, using the same multilevel edge-based features with video sequence level adaptation producing about 99% performance.
Node level adaptation could be applied to add capacity by powering on a node.
The second level adaptation provides a single parameter vector for the controller.
A multi-input multi-output (MIMO) version of second level adaptation using multiple models is developed.
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It provides an algorithm-level adaptation and is capable of dynamically adapting to appropriate prefetching algorithms at runtime.
The results of the experiment indicate that humans respond well to motion-level adaptation, even with very limited training and without being informed the robot is adaptive.
The evaluation of human response to adaptive robotic assistants has been limited, particularly in the realm of motion-level adaptation.
It's a group-level adaptation.
Multi-Level: Adaptation needs planning and action at multiple levels — national, state, local and project-level.
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