On the pinning strategy of complex networks

In pinning control of complex networks, a tacit believing is that the system dynamics will be better controlled by pinning the large-degree nodes than the small-degree ones. Here, by changing the number of pinned nodes, we find that, when a significant fraction of the network nodes are pinned, pinning the small-degree nodes could generally have a higher performance than pinning the large-degree nodes. We demonstrate this interesting phenomenon on a variety of complex networks, and analyze the underlying mechanisms by the model of star networks. By changing the network properties, we also find that, comparing to densely connected homogeneous networks, the advantage of the small-degree pinning strategy is more distinct in sparsely connected heterogenous networks

Bayesian Flexible Modeling of Interval-censored Failure Time Data

Interval-censored data are a special type of survival data, in which the survival time is not accurately observed but known to fall within a specific time interval. Interval censored data commonly arise in real-life epidemiological and medical studies that involve periodic examinations. In this dissertation, several semi-parametric regression models are investigated to provide flexible modeling and robust inference for interval censored data from Bayesian perspectives. Chapter 1 provides a detailed description about interval-censored data and gives several examples. Existing models and methods for analyzing such interval-censored data are reviewed as well. Chapter 2 develops a unified Bayesian estimation approach under the framework of semi-parametric linear transformation models for regression analysis of current status data, which is a special type of interval-censored data. This work provides an alternative estimation approach to the existing methods for the proportional hazards, proportional odds, and probit models. As a unified Bayesian estimation approach, the proposed method allows direct comparison of three different semi-parametric regression models in the same framework of the Gibbs Sampler. Chapter 3 proposes a Bayesian estimation approach for analyzing general interval censored data under the generalized odds-rate hazards (GORH) models. The GORH models are a general class of semi-parametric regression models including the proportional hazards and proportional odds models as special cases. Submodels of GORH models can be specified by indexing a non-negative value v, where the sub prefix refers to the fact that for each v, a semi-parametric regression model is well-specified for regression analysis of general interval-censored data. It is found that treating v as an unknown parameter leads to biased estimation, which in this case is a consistent research result for right-censored data in the literature. To solve this issue, a Bayesian approach with a known v is proposed and has shown excellent performance in the simulation study. Chapter 4 extends the semi-parametric probit model for regression analysis of arbitrarily censored data. The proposed method has been implemented using two sets of latent variables for posterior computation. The proposed method can be easy to implement in the estimation of regression parameters for two special types of arbitrarily censored data: right-censored data and general interval-censored data

Time-reversal-symmetry-broken quantum spin Hall effect

Quantum spin Hall (QSH) state of matter is usually considered to be protected by time-reversal (TR) symmetry. We investigate the fate of the QSH effect in the presence of the Rashba spin-orbit coupling and an exchange field, which break both inversion and TR symmetries. It is found that the QSH state characterized by nonzero spin Chern numbers $C_{\pm}=\pm 1$ persists when the TR symmetry is broken. A topological phase transition from the TR symmetry-broken QSH phase to a quantum anomalous Hall phase occurs at a critical exchange field, where the bulk band gap just closes. It is also shown that the transition from the TR symmetry-broken QSH phase to an ordinary insulator state can not happen without closing the band gap.Comment: 5 pages, 5 figure

Preamble design using embedded signalling for OFDM broadcast systems based on reduced-complexity distance detection

The second generation digital terrestrial television broadcasting standard (DVB-T2) adopts the so-called P1 symbol as the preamble for initial synchronization. The P1 symbol also carries a number of basic transmission parameters, including the fast Fourier transform size and the single-input/single-output as well as multiple-input/single-output mode, in order to appropriately configure the receiver for carrying out the subsequent processing. In this contribution, an improved preamble design is proposed, where a pair of training sequences is inserted in the frequency domain and their distance is used for transmission parameter signalling. At the receiver, only a low-complexity correlator is required for the detection of the signalling. Both the coarse carrier frequency offset and the signalling can be simultaneously estimated by detecting the above-mentioned correlation. Compared to the standardised P1 symbol, the proposed preamble design significantly reduces the complexity of the receiver while retaining high robustness in frequency-selective fading channels. Furthermore, we demonstrate that the proposed preamble design achieves a better signalling performance than the standardised P1 symbol, despite reducing the numbers of multiplications and additions by about 40% and 20%, respectively