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The ability to reconstruct complex networks plays an important role in our understanding of how nodes interact with each other and how information flows coordinate node's dynamic behaviors. Many similarity-based methods usually prefer steady-state data to time-series and perform poorly with the latter, such as pearson correlation and mutual information. Meanwhile, these similarity-based methods result...
To identify the structure of networks is essential for analysis of complex networks. This paper transforms network reconstruction to be a signal recovery problem by means of compressive sensing. In the literature, the sensing matrix is determined by the network dynamic and measured states of nodes, which might violates the restriction on the coherence of the sensing matrix for exact recovery. This...
In order to improve the robustness and anti-interference ability of induction motor variable frequency speed control system (IMVFSCS), a modified internal model control (MIMC) method based on neural network generalized inverse (NNGI) was proposed. On the basis of reversibility analysis of original system, the generalized inverse model approximated by the dynamical BP neural network was cascaded with...
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