A fast algorithm to formulate Markov system equations

In this paper a new and efficient algorithm is presented to formulate a set of equations corresponding to a system with repair without pass through Markov graphs [1,2]. Using Karnaugh maps [3] for the states of the system and by the introduction of the concept of contiguous states, a basic method by inspection is derived. The hazard rates are assumed to be constant.     

Mie散射系数的新算法

介绍了一种计算Ｍｉｅ散射系数的新方法，给出了计算实例。     

TD-SCDMA系统中基于上行参数的下行波束赋形算法

在TD－SCDMA系统中，我们在基站发送端进行波束赋形来提高下行链路的性能。以最优准则－最大信干噪比特征分解算法为例，我们分析基于上行参数进行下行赋形的基本原理，模拟了不同环境下赋形算法的性能，并与全向情况进行比较，得出了相应的结论。     

基于马尔科夫的聚类算法仿真分析

针对传统k均值聚类算法易受初始条件影响的问题,文中在已有聚类算法的基础上提出了一个新型的图型聚类算法:马尔科夫(MCL)聚类算法。通过MATLAB仿真软件对空手道俱乐部数据用马尔科夫聚类算法进行仿真分析,得出聚类结果,并同时分析参数对算法性能的影响。实验结果表明,马尔科夫聚类算法可以应用于对图的聚类中,但同时也会受到参数的影响。     

New code parameters from Reed-Solomon subfield codes

We determine the dimensions of subfield codes of Reed-Solomon codes and construct certain extensions and lengthenings of these codes. We start from the duals, using the language of orthogonal arrays. As a first result this allows us to obtain a fair number of improvements in the list of binary, ternary, and quaternary linear codes with largest known minimal distance     

Time moments and Markov parameters of composite systems

A theorem is given to show that a reduced-order composite system, formed from the interconnection of a number of reduced-order models that are Padé-type approximants of some subsystems, matches the initial time moments and Markov parameters of the composite system formed from the interconnection of these subsystems. Thus the reduced-order composite system has the same tracking properties as the original composite system.     

Prediction of channel parameters from amplitude-only data using prony algorithm

Proposed is a new technique based on the Prony algorithm that utilises amplitude-only data to estimate relative delays and amplitudes of the multipath rays. The use of amplitude-only data instead of complex data in the estimation process reduces the complexity and cost of the data measurement and acquisition systems. The theoretical analysis is validated by computer simulation and experimental measurement. Prediction of the different parameters showed very good agreement with actual values.     

Realizations of two-parameter functions using Markov parameters and moments

An algorithm for determining a minimal state variable realization for two-variable transfer functions using a combination of newly defined Markov parameters and moments of impulse response matrix has been described.     

Markov隐写检测特征的一种新设计

如何在保持Markov特征隐写检测能力的同时降低其维数是隐写分析领域中一个重要问题。该文通过将空域图像各向同性的统计假设扩展到离散余弦变换(DCT)域,给出了一种新的特征设计方法。该方法可将传统的块内特征的维数降低36%,块间特征的维数降低72%,且广泛地适用于不同提取源不同阶数的Markov特征。实验表明,该文的设计方法降低维数的同时还提高了特征的检测性能。     

Phased-mission system reliability under Markov environment

The authors show how to determine the reliability of a multi-phase mission system whose configuration changes during consecutive time periods, assuming failure and repair times of components are exponentially distributed and redundant components are repairable as long as the system is operational. The mission reliability is obtained for 3 cases, based on a Markov model. (1) Phase durations are deterministic; the computational compact set model is formulated and a programmable solution is developed using eigenvalues of reduced transition-rate matrices. (2) Phase durations are random variables of exponential distributions and the mission is required to be completed within a time limit; the solution is derived as a recursive formula, using the result of case 1 and mathematical treatment-a closed-form solution would be prohibitively complex and laborious to program. (3) Phase durations are random variables and there is no completion time requirement; the solution is derived similarly to case 1 using moment generating functions of phase durations. Generally, reliability problems of phased-mission systems are complex. The authors' method provides exact solutions which can be easily implemented on a computer     

A de-interlacing algorithm using Markov random field model.

In this paper, a motion-compensated de-interlacing algorithm using the Markov random field (MRF) model is proposed. The de-interlacing problem is formulated as a maximum a posteriori (MAP) MRF problem. The MAP solution is the one that minimizes an energy function, which imposes discontinuity-adaptive smoothness (DAS) spatial constraint on the de-interlaced frame. The edge direction information, which is used to formulate the DAS constraint, is implicitly indicated by weight vectors (weights for 16 digitized directions). Generally, large weights are assigned to along-edge directions and relatively small weights are assigned to across-edge directions. As a local statistical-based method, the proposed weighting method should be more robust than traditional edge-directed interpolation methods in deciding local edge directions. The proposed algorithm is implemented by an iterative optimization process, which guarantees convergence. However, a global optimal solution is not guaranteed due to computational complexity concern. Simulation results compare the proposed algorithm to other motion compensated de-interlacing algorithms. Significant improvements of de-interlaced edges are observed.     

A wavelet-based algorithm to estimate ocean wave group parameters from radar images

In recent years, new remote sensing techniques have been developed to measure two-dimensional (2-D) sea surface elevation fields. The availability of these data has led to the necessity to extend the classical analysis methods for one-dimensional (1-D) buoy time series to two dimensions. This paper is concerned with the derivation of group parameters from 2-D sea surface elevation fields using a wavelet-based technique. Wave grouping is known to be an important factor in ship and offshore safety, as it plays a role in dangerous resonance phenomenons and the generation of extreme waves. Synthetic aperture radar (SAR) data are used for the analysis. The wavelet technique is introduced using synthetic ocean surfaces and simulated SAR data. It is shown that the group structure of the ocean wave field can be recovered from the SAR image if the nonlinear imaging effects are moderate. The method is applied to a global dataset of European Remote Sensing satellite (ERS-2) wave mode data. Different group parameters including the area covered by the largest group and the number of groups in a given area are calculated for over 33 000 SAR images. Global maps of the parameters are presented. For comparison, classical 1-D grouping parameters are calculated from colocated wave model data showing good overall agreement with the wavelet-derived parameters. ERS-2 image mode data are used to study wave fields in coastal areas. Waves approaching the island of Sylt in the North Sea are investigated, showing the potential of the wavelet technique to analyze the spatial wave dynamics associated with the bottom topography. Observations concerning changes of wavelength and group parameters are compared to linear wave theory.     

求解多输入多输出检测新算法——遗传粒子群优化

设计两种基于粒子群优化算法（PSO）和基于遗传算法（GA）的多输入多输出（MIMO）系统检测算法。提出一种新的融合GA和PSO进化机制的遗传粒子群进化（GPSO）算法,并将其应用于MIMO系统检测问题求解。新算法改善了初始化种群,并将每一代粒子划为精英粒子、次优粒子和糟糕粒子三部分,对这三种粒子分别采用极值扰动、PSO进化和淘汰策略以改善算法的全局和局部搜索能力,从而加快算法的寻优速率和收敛速度。仿真结果表明：与基于PSO和基于GA的检测算法相比,GPSO的检测算法能够很大程度减少种群规模和迭代次数。而与最优的最大似然译码算法相比,GPSO检测算法能够在计算复杂度和误码性能之间获得很好的折中。     

New LSCM blind multiuser detection algorithm for antenna array CDMA system

Two blind multiuser detection algorithms for antenna array in Code Division Multiple Access （CDMA） system which apply the linearly constrained condition to the Least Squares Constant Modulus Algorithln （LSCMA） are proposed in this paper. One is the Linearly Constrained LSCMA （LC-LSCMA）, the other is the Preprocessing LC-LSCMA （PLC-LSCMA）. The two algorithms are compared with the conventional LSCMA. The results show that the two algorithms proposed in this paper are superior to the conventional LSCMA and the best one is PLC-LSCMA.     

基于Markov链安全性的量化隐写算法

如何在大容量嵌入的同时保证隐秘信息的统计安全性是当前隐写算法设计的难点和热点。本文证明了载体图像Markov链(MC)二阶统计特性的保持等价于其一阶统计特性保持的结论,并据此以MC安全标准为优化目标,提出二阶安全的图像预测误差量化隐写算法。实验表明,在较大容量的数据嵌入过程中,该算法能很好保持二阶统计特性,取得隐写安全性的提高。     

一种基于非均匀马尔可夫随机场的图像分割方法

提出了一种新的基于非均匀马尔可夫随机场(MRF)的图像分割算法。基于非均匀马尔可夫随机场的图像分割的关键是对MRF中耦合系数的估计。本文结合四叉树分解提出了一种新的非均匀MRF的耦合系数估计方法。先对图像用传统的MRF分割方法进行预分割,再在预分割的基础上用边缘检测算子检验出预分割图像中的边缘,再利用图像的边缘信息对图像进行四叉树分解,把图像分成不同大小的子块。再根据每个子块的大小,估计出非均匀MRF的耦合系数。实验表明,将本文方法估计出来的耦合系数应用到分割算法中去,能明显改善图像分割的效果,而且具有更好的自适应性。     

A joint-optimization NSAF algorithm based on the first-order Markov model

Recently, the normalized subband adaptive filter (NSAF) algorithm has attracted much attention for handling colored input signals. Based on the first-order Markov model of the optimal weight vector, this paper provides some insights for the convergence of the standard NSAF. Following these insights, both the step size and the regularization parameter in the NSAF are jointly optimized by minimizing the mean-square deviation. The resulting joint-optimization step size and regularization parameter algorithm achieves a good tradeoff between fast convergence rate and low steady-state error. Simulation results in the context of acoustic echo cancelation demonstrate good features of the proposed algorithm.     

基于核函数法及马尔可夫链的节点定位算法

基于贝叶斯滤波框架,提出了基于核函数法及马尔可夫链的节点定位算法,该算法采用射频指纹匹配技术,使用核函数构建似然函数,充分利用观测与多个训练样本之间的相似性,避免使用先验确定型信号分布模型产生的误差.此外,为提高移动目标的定位精度和定位实时性,该算法还使用马尔可夫链,通过利用目标的历史状态和环境布局等信息对匹配定位的网格搜索空间进行限制,剔除目标移动过程中不可能发生的位置跳变.实验证明,与高斯分布模型相比,所提定位算法具有更高的定位正确率和定位精度.     

基才隐马尔可夫模型的蛋白质序列筛选算法

对蛋白质序列筛选算法进行了研究,针对蛋白质数据库中存在大量的冗余序列,提出了一种基于隐马尔可夫模型的蛋白质序列筛选算法。详细阐述了在蛋白质数据库中如何建立隐马尔可夫模型。对模型中主要参数的求解和估计给出了主要计算公式。然后利用所建立的模型对蛋白质数据库进行的序列筛选测试,测试结果表明本文设计的算法对同源蛋白质序列筛选精...