Random Classical Fidelity

We introduce a random perturbed version of the classical fidelity and we show that it converges with the same rate of decay of correlations, but not uniformly in the noise. This makes the classical fidelity unstable in the zero-noise limit.     

Moderate Deviations for Longest Increasing Subsequences: The Lower Tail

We derive a moderate deviation principle for the lower tail probabilities of the length of a longest increasing subsequence in a random permutation. It refers to the regime between the lower tail large deviation regime and the central limit regime. The present article together with the upper tail moderate deviation principle in Ref. 12 yields a complete picture for the whole moderate deviation regime. Other than in Ref. 12, we can directly apply estimates by Baik, Deift, and Johansson, who obtained a (non-standard) Central Limit Theorem for the same quantity.     

A parametric representation of linguistic hedges in Zadeh’s fuzzy logic

This paper proposes a model for the parametric representation of linguistic hedges in Zadeh’s fuzzy logic. In this model each linguistic truth-value, which is generated from a primary term of the linguistic truth variable, is identified by a real number r depending on the primary term. It is shown that the model yields a method of efficiently computing linguistic truth expressions accompanied with a rich algebraic structure of the linguistic truth domain, namely De Morgan algebra. Also, a fuzzy logic based on the parametric representation of linguistic truth-values is introduced.     

One-dimensional non-nearest-neighbor random walks in the presence of traps

A one-dimensional lattice random walk in the presence ofm equally spaced traps is considered. The step length distribution is a symmetric exponential. An explicit analytic expression is obtained for the probability that the random walk will be trapped at thejth trapping site.     

Study on the possibilities of controlling the laser output beam properties by an intracavity deformable mirror

The possibilities of controlling the laser beam properties by a deformable mirror introduced into the laser optical cavity were studied theoretically and experimentally. The experiments were performed under conditions of an industrial high power transverse flow cw CO₂ laser operating with a stable resonator of a folded configuration. A deformable bimorph mirror of a surface profile controlled by the voltage applied to the mirror electrodes is implemented to the laser system as a back cavity mirror or as a one of the inner folding mirrors. The near-and far-field characteristics of the laser beam versus the resonator configuration controlled by the changes of the focal length of the deformable mirror are discussed in the paper. The analysis reveals that the resonator with an inner deformable mirror is much more sensitive to the mirror curvature variations than the resonator in which the deformable mirror is used as a back cavity mirror. The presented results show that dynamic and controllable changes in the resonator properties result in the controlled modification and optimisation of the laser output power and spatial parameters of the laser radiation.     

Performance Enhancement for Optical Fast Frequency-hopping CDMA Systems by BCH Channel Coding

In this paper, the impact of optical beat noise on the performance of optical fast frequency-hopping code-division multiple-access (FFH OCDMA) networks is analyzed. BCH/FFH-OCDMA to reduce the impact of optical beat noise is proposed. It is shown that, BCH/FFH-OCDMA has much better performance under the same bit rate, same chip time and same number of available wavelengths. Another advantage for BCH/FFH-OCDMA is that the code length of one-coincidence sequence will be shorter, which can greatly reduce the difficulty of fabrication for fiber gratings.     

平面上随机级数的性质

研究了平面上系数{Xn,n≥0}为(?)-混合序列在满足,(q>1)等条件下的随机级数的增长性及值分布,得到了比较好的结果．     

Bayesian Prediction Analysis for Growth Curve Model Using Noninformative Priors

We apply a Bayesian approach to the problem of prediction in an unbalanced growth curve model using noninformative priors. Due to the complexity of the model, no analytic forms of the predictive densities are available. We propose both approximations and a prediction-oriented Metropolis-Hastings sampling algorithm for two types of prediction, namely the prediction of future observations for a new subject and the prediction of future values for a partially observed subject. They are illustrated and compared through real data and simulation studies. Two of the approximations compare favorably with the approximation in Fearn (1975, Biometrika, 62, 89–100) and are very comparable to the more accurate Rao-Blackwellization from Metropolis-Hastings sampling algorithm.     

液体可视图象序列中杂质小目标的检测方法

在分析红外图象和视图象差异的基础上，研究了一种适用于可视图像序列的运动小目标检测算法。受目标影响的象素点具有较弱的时间相关性，即相对普通象素点有较大的时间方差，根据此特征，用管道更新的方法产生新方差图象序列，再用管道更新的方法累积，增加信噪比，然后用基于统计均值的自适应门限方法分割出目标，最后将原图象的梯度倒数作为象素点强度的加权，有效地抑制灰度突变边界的传感器噪音，保存目标点。     

Phase Transition in Vertex-Reinforced Random Walks on {\mathbb{Z}} with Non-linear Reinforcement

Vertex-reinforced random walk is a random process which visits a site with probability proportional to the weight w _k of the number k of previous visits. We show that if w _k ∼ k ^α, then there is a large time T ₀ such that after T ₀ the walk visits 2, 5, or ∞ sites when α < 1, = 1, or > 1, respectively. More general results are also proven.