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Reinforcement Learning aims to find the optimal decision in uncertain environments on the basis of qualitative and noisy on-line performance feedback provided by the environments. During the past four decades, learning theory has grown into a vast field in which a very large number of problems have been studied. One of the primary limitations of reinforcement schemes, acknowledged by workers in the...
Second level adaptation using multiple models for the adaptive control of linear systems with unknown parameters was introduced in [1], and its robustness properties were discussed in [2]. In both cases, the plant, the identification models, and the reference model were assumed to be described by state equations in companion form, with all state variables accessible.
In the traditional Mean Shift tracking algorithm, The Bhattacharyya coefficient is an efficient method in image statistical feature matching. But for the influence of background feature, the optimal location obtained by Bhattacharyya coefficient may not be the exact target location. Thus, there will be drifted or even wrong location in tracking. This paper proposes an improved Bhattacharyya coefficient...
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