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Many complex systems can be represented as networks composed of different types of interactions, which are categorized as links belonging to different layers, forming multiplex networks (MNs). In order to simplify the study of MNs...
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Many complex systems can be represented as networks composed of different types of interactions, which are categorized as links belonging to different layers, forming multiplex networks (MNs). In order to simplify the study of MNs, many methods for aggregating MNs have been proposed, but the aggregation of MNs still faces two challenges. The first one is how to measure the destruction of original MN's structure after they are aggregated and the other is how to meet different requirements for the integrity of network structures for different studies. For the first one, we design an efficient and novelty index named as similarity of MNs (SMNs) for measuring the MN's structural similarity between original and simplified MNs. For the second one, a method for aggregating MNs, named as AMNs, is proposed to compromise the simplification and maintain the core structure of MNs. Several representative synthetic networks are used to evaluate the reliability of AMNs. Moreover, AMNs is applied to some real-life MNs, including biology, human society, and transportation MNs. Experimental results demonstrate positively that the proposed approach AMNs can simplify the MNs effectively under different requirements. (C) 2019 Elsevier B.V. All rights reserved.
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In this paper, hybrid models for the design and optimization of large-scale multiplexers are presented. First, analysis based on the low-pass prototype filter circuit model proves that the first cavity of a channel filter next to ...
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In this paper, hybrid models for the design and optimization of large-scale multiplexers are presented. First, analysis based on the low-pass prototype filter circuit model proves that the first cavity of a channel filter next to the manifold is critical in the design of multiplexers. A hybrid model is proposed, combining a circuit model and the electromagnetic (EM) analysis of the coupling junction close to the manifold. The fact that only a single junction requires EM simulation facilitates the introduction of neural networks to multiplexer design for the first time. Another format of the hybrid model is then built by replacing the EM simulation with a neural model for the output coupling to the first resonator. The efficiency of the method is demonstrated using a six-channel multiplexer and a 13-channel multiplexer. Responses predicted by the hybrid models agree well with full EM simulations and measurement results. The proposed hybrid models are proven to be able to provide a high degree of accuracy in both in-band and out-of-band frequency ranges and fast, enabling iterative optimization involving all design parameters for large-scale multiplexers.
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Relay selection strategies help to improve spectral and energy efficiencies, to enhance transmission robustness, or to reduce latency in multi-relay cooperative networks. Two novel relay selection strategies are proposed and analy...
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Relay selection strategies help to improve spectral and energy efficiencies, to enhance transmission robustness, or to reduce latency in multi-relay cooperative networks. Two novel relay selection strategies are proposed and analyzed here for multiple-input multiple-output (MIMO) amplify-and-forward (AF) two-way relay networks (TWRNs) with spatial multiplexing. Specifically, they are designed to maximize the effective end-to-end signal-to-noise ratio (SNR), and thereby minimize the overall outage probability or maximize the achievable sum rate. Interestingly, the first strategy amounts to maximizing the minimum of the eigenvalues of the Wishart matrices from the selected relay to the two user nodes. Counter-intuitively, the latter strategy amounts to maximizing the minimum of the determinant of the same Wishart matrices. The performance of these two strategies is investigated by deriving lower/upper bounds of the overall outage probability and the average sum rate approximations in closed form. Further, the asymptotic high-SNR approximations of the outage probability are derived, and thereby, the achievable diversity-multiplexing tradeoff is quantified. This tradeoff reveals that whenever the sum of relay antennas is fixed, the achievable diversity order is always a constant, and hence, the multiplexing gain can indeed be improved by equally distributing antennas among the available set of relays. Our results reveal that relay selection indeed significantly alleviates the inherent diversity-gain loss associated with the use of available degrees of freedom for spatial multiplexing.
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Real world complex systems have multiple levels of relationships and in many cases, they need to be modeled as multiplex networks where the same nodes can interact with each other in different layers, such as social networks. Howe...
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Real world complex systems have multiple levels of relationships and in many cases, they need to be modeled as multiplex networks where the same nodes can interact with each other in different layers, such as social networks. However, social relationships only appear at prescribed times so the temporal structures of edge activations can also affect the dynamical processes located above them. To consider both factors are simultaneously, we introduce multiplex temporal networks and propose three different walk strategies to investigate the concurrent dynamics of random walks and the temporal structure of multiplex networks. Thus, we derive analytical results for the multiplex centrality and coverage function in multiplex temporal networks. By comparing them with the numerical results, we show how the underlying topology of the layers and the walk strategy affect the efficiency when exploring the networks. In particular, the most interesting result is the emergence of a super-diffusion process, where the time scale of the multiplex is faster than that of both layers acting separately. (C) 2016 Elsevier B.V. All rights reserved.
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Network embedding (or graph embedding) has been widely used in many real-world applications. However, existing methods mainly focus on networks with single-typed nodes/edges and cannot scale well to handle large networks. Many rea...
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Network embedding (or graph embedding) has been widely used in many real-world applications. However, existing methods mainly focus on networks with single-typed nodes/edges and cannot scale well to handle large networks. Many real-world networks consist of billions of nodes and edges of multiple types, and each node is associated with different attributes. In this paper, we formalize the problem of embedding learning for the Attributed Multiplex Heterogeneous Network and propose a unified framework to address this problem. The framework supports both transductive and inductive learning. We also give the theoretical analysis of the proposed framework, showing its connection with previous works and proving its better expressiveness. We conduct systematical evaluations for the proposed framework on four different genres of challenging datasets: Amazon, YouTube, Twitter, and Alibaba1. Experimental results demonstrate that with the learned embeddings from the proposed framework, we can achieve statistically significant improvements (e.g., 5.99-28.23% lift by F1 scores; p < 0.01, t-test) over previous state-of-the-art methods for link prediction. The framework has also been successfully deployed on the recommendation system of a worldwide leading e-commerce company, Alibaba Group. Results of the offline A/B tests on product recommendation further confirm the effectiveness and efficiency of the framework in practice.
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Quantum transport through disordered structures is inhibited by localized eigenstates of the Hamiltonian associated with the network. We show how to overcome localization by network multiplexing. Here, multiple layers of random ne...
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Quantum transport through disordered structures is inhibited by localized eigenstates of the Hamiltonian associated with the network. We show how to overcome localization by network multiplexing. Here, multiple layers of random networks with the same number of nodes are stacked in such a way that in the perpendicular directions regular one-dimensional networks are formed. Depending on the ratio of the coupling within the layer and perpendicular to it, transport gets either enhanced or diminished. In particular, if the couplings are of the same order, transport gets enhanced and localization effects can be overcome. We exemplify our results by multiplexes of random networks, where the disorder is topological.
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Isolated complex networks have been studied deeply in the last decades due to the fact that many real systems can be modeled using these types of structures. However, it is well known that the behavior of a system not only depends...
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Isolated complex networks have been studied deeply in the last decades due to the fact that many real systems can be modeled using these types of structures. However, it is well known that the behavior of a system not only depends on itself, but usually also depends on the dynamics of other structures. For this reason, interacting complex networks and the processes developed on them have been the focus of study of many researches in the last years. One of the most studied subjects in this type of structures is the Synchronization problem, which is important in a wide variety of processes in real systems. In this manuscript we study the synchronization of two interacting scale-free networks, in which each node has ke dependency links with different nodes in the other network. We map the synchronization problem with an interface growth, by studying the fluctuations in the steady state of a scalar field defined in both networks.
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Synchronization phenomenon plays an important role in the dynamic process on complex networks. In this letter, we consider synchronization under multiplex structures and explore the effect of external parts on the multilayered Kur...
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Synchronization phenomenon plays an important role in the dynamic process on complex networks. In this letter, we consider synchronization under multiplex structures and explore the effect of external parts on the multilayered Kuramoto model with positive correlation between frequencies and degree. We show that large and strong mixing parts of the external layer may put off synchronization while the coupling strength of external layers has an accelerating, but limited, influence on synchronization. In particular, an explosive synchronization can be obtained by weakening the co-evolution coupling strength. The transition tends to be smooth when the co-evolution coupling strength increases. Our findings indicate that externality from multiplex networks, especially the mixing parts, and the co-evolution coupling strength should be of importance for synchronization on one certain layer.
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In this paper we study the dynamics of a multiplex multilayer network, where each layer is composed of identical Kuramoto-Sakaguchi phase oscillators with nonlocal coupling. We focus on a three-layer multiplex network and observe ...
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In this paper we study the dynamics of a multiplex multilayer network, where each layer is composed of identical Kuramoto-Sakaguchi phase oscillators with nonlocal coupling. We focus on a three-layer multiplex network and observe a specific form of multiplex network behavior, the macroscopic chimeralike state. It is decomposed by a splitting of the layers with initially close dynamics into subgroups. The first group consists of two layers performing one type of dynamics, whereas the rest perform the other type, after the introduction of interlayer coupling. Based on an intensive computational analysis, we show that areas of macroscopic chimeralike states are observed close to the critical transition points of intralayer (microscopic) states in the parameter space. We find that this macroscopic chimeralike state is excited at weak and medium interlayer coupling strength, wherein the interlayer phase lag here plays an important role, since this is a network parameter which controls macroscopic dynamics and transforms boundaries between intralayer states. The obtained numerical results are validated analytically by considering the multiplex network dynamics using the Ott-Antonsen reduction of the governing network equations.
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A new approach for designing a microwave multiplexing network is presented in order to improve channel performance. Through design and optimization of the connecting transmission line structure, the new approach ensures that an ex...
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A new approach for designing a microwave multiplexing network is presented in order to improve channel performance. Through design and optimization of the connecting transmission line structure, the new approach ensures that an extra pole is formed in the passband of each channel. The channel filter order is therefore increased by one without additional resonators. Significant improvement in the performance of the multiplexer is achieved without the penalty of increased size or weight of the hardware, which is extremely important for applications in communication satellite. Simulation and measurement results are used to demonstrate the feasibility of such enhanced microwave multiplexing networks.
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