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In this paper, we consider the privacy preserving problem in an agreement network under interception attacks. First, we introduce a consensus protocol with privacy preserving, where each node hides their initial states into a set of random sequences, and then injects the sequences into the process of consensus. Second, we assume that an attacker with limited power can intercept the data transmitted...
In this paper, we consider the privacy preserving problem of consensus protocol. First, we introduce a privacy preserving scheme, where each node produces and transmits a sequence of random values with their mean equaling to the node's initial state. We show that the network can reach average consensus with privacy preserving scheme, and provide a sufficient condition under which the initial state...
The role of learning gains in the ability of a computational framework to better capture the behaviour of human motor control in learning and executing a task is the subject of discussion in this paper. In our previous work, a computational model for human motor learning of a task through repetition was established and its convergence analysed. In this paper, the performance of the model is investigated...
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