is paper puts forward a method to design the H ∞ filter for networked control systems (NCSs) with time delay and data packet loss. Based on the properties of Markovian jump system, the packet loss is treated as a constant probability independent and identically distributed Bernoulli random process. us, the stochastic stability condition can be acquired for the filtering error system, which meets an H ∞ performance index level c. It is shown that, by introducing a special structure of the relaxation matrix, a linear representation of the filter meeting an H ∞ performance index level for NCSs with time delay and packet loss can be obtained, which uses linear matrix inequalities (LMIs). Finally, numerical simulation examples demonstrate the effectiveness of the proposed method.Hindawi
Presently, most of the existing rumor detection methods focus on learning and integrating various features for detection, but due to the complexity of the language, these models often rarely consider the relationship between the parts of speech. For the first time, this paper integrated a knowledge graphs and graph attention networks to solve this problem through attention mechanisms. A knowledge graphs can be the most effective and intuitive expression of relationships between entities, providing problem analysis from the perspective of “relationships”. This paper used knowledge graphs to enhance topics and learn the text features by using self-attention. Furthermore, this paper defined a common dependent tree structure, and then the ordinary dependency trees were reshaped to make it generate a motif-dependent tree. A graph attention network was adopted to collect feature representations derived from the corresponding syntax-dependent tree production. The attention mechanism was an allocation mechanism of weight parameters that could help the model capture important information. Rumors were then detected accordingly by using the attention mechanism to combine text representations learned from self-attention and graph representations learned from the graph attention network. Finally, numerous experiments were performed on the standard dataset Twitter, and the proposed model here had achieved a 7.7% improved accuracy rate compared with the benchmark model.
This paper investigates a modified modeling of networked control systems (NCSs) with programmable logic controller (PLC). First, the controller-to-actuator and sensor-to-controller network-induced delays are investigated by a modeling tactics based on hierarchical coloured petri net (HCPN) in a structure-conserving way. Comparing with the recent result, the signal transmission delay is set in a random interval instead of a fixed mode; moreover, the data packet drop out and disorder are also taken into consideration. Second, delays captured form CPN tools are analyzed with a strategy based on Baum–Welch algorithm and statistics science. Besides, time delays are modeled as a Markov chain and the transition probabilities is calculated using the consequent from the previous operation. Finally, a comparison verification illustrates the equivalence property between proposed models.
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