15,587 research outputs found
Analytical controllability of deterministic scale-free networks and Cayley trees
According to the exact controllability theory, the controllability is
investigated analytically for two typical types of self-similar bipartite
networks, i.e., the classic deterministic scale-free networks and Cayley trees.
Due to their self-similarity, the analytical results of the exact
controllability are obtained, and the minimum sets of driver nodes (drivers)
are also identified by elementary transformations on adjacency matrices. For
these two types of undirected networks, no matter their links are unweighted or
(nonzero) weighted, the controllability of networks and the configuration of
drivers remain the same, showing a robustness to the link weights. These
results have implications for the control of real networked systems with
self-similarity.Comment: 7 pages, 4 figures, 1 table; revised manuscript; added discussion
about the general case of DSFN; added 3 reference
Structural Analysis of Network Traffic Matrix via Relaxed Principal Component Pursuit
The network traffic matrix is widely used in network operation and
management. It is therefore of crucial importance to analyze the components and
the structure of the network traffic matrix, for which several mathematical
approaches such as Principal Component Analysis (PCA) were proposed. In this
paper, we first argue that PCA performs poorly for analyzing traffic matrix
that is polluted by large volume anomalies, and then propose a new
decomposition model for the network traffic matrix. According to this model, we
carry out the structural analysis by decomposing the network traffic matrix
into three sub-matrices, namely, the deterministic traffic, the anomaly traffic
and the noise traffic matrix, which is similar to the Robust Principal
Component Analysis (RPCA) problem previously studied in [13]. Based on the
Relaxed Principal Component Pursuit (Relaxed PCP) method and the Accelerated
Proximal Gradient (APG) algorithm, we present an iterative approach for
decomposing a traffic matrix, and demonstrate its efficiency and flexibility by
experimental results. Finally, we further discuss several features of the
deterministic and noise traffic. Our study develops a novel method for the
problem of structural analysis of the traffic matrix, which is robust against
pollution of large volume anomalies.Comment: Accepted to Elsevier Computer Network
Design of Compact Planar Diplexer Based on Novel Spiral-Based Resonators
A miniaturized planar diplexer utilizing the novel spiral-based resonators is proposed. The given cell which is initially proposed in this article is composed of two separated rectangular spirals which are asymmetrical to each other and thus, it is called as ‘asymmetrical separated spirals resonator’ (ASSR). ASSR has more superior transmission property than the previous prototype and extremely compact dimension is also achieved. It is demonstrated that ASSR can exhibit bandpass performance with high frequency selectivity and good transmission property within the relatively low frequency band. Based on the given characteristic, one planar diplexer composed of T-junction and two ASSRs is synthesized and the fabricated prototype with compact dimension is achieved, thanks to ASSRs explored. Simultaneously, the transversal dimension of each channel is extremely compact because ASSRs are completely embedded in the feed lines. Both the simulated and measured results indicate that satisfactory impedance matching and high isolation between two channels are achieved. Furthermore, the proposed diplexer is uniplanar and no defected ground structure is introduced
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