分布式环境下基于马尔科夫链的图流三角近似计算

图三角数量的计算是计算网络聚集系数和传递性的重要步骤.大数据背景下,以采样为策略的近似计算成为图三角计算的主要方法,然而此类方法面临时空消耗和计算错误性两大难题.本文提出了一种针对图流的基于马尔科夫链的图三角近似计算算法,该算法以窗口作为图流处理单位,将马尔科夫链与采样相结合,保证降低错误率的同时实现动态适应内存空间的变化.实验显示,相较其他三角形近似计算算法,该算法在错误率上降低2~4倍,时间消耗上也有很大改进.     

基于条件独立测试的链图结构学习算法

链图是贝叶斯网络和马尔科夫网络的自然推广,具有较强的表达能力.但目前关于链图结构学习算法的研究较少.本文基于贝叶斯网络结构学习的Grow-Shrink算法思想,提出一种链图等价类结构学习算法.该算法首先利用网络中结点的局部邻域信息,学习结点的邻接结点恢复网络骨架;然后根据链图复合体有向边的特点,利用条件独立测试确定网络的复合体有向边,从而恢复链图结构.理论分析和实验结果表明了该算法的正确性和有效性.     

Analysis of the fundamental error statistics in DPSK systems using a Markov chain model (Corresp.)

Finite-state Markov chain models are proposed to represent the process of the occurrence of errors in differential phase-shift-keying (DPSK) systems and also in coherent phase-shift-keying (CPSK) systems with differential coding-and-decoding schemes. A simple and general formula is derived for the probabilityP(m,n)of the occurrence of m errors in a sequence ofndigits which is the fundamental error statistic required to evaluate random-error-correcting codes applied to these channels.     

卷积码的因子图解码算法研究

因子图是一种双向图，它描述了一种用本地函数来表达全局函数的算法。因子图连同积和算法是通信中强有力的工具。现提出了一种新的解码算法，即将因予图与积和算法应用在通信系统的解码中，并通过仿真，寻找到了一个更新次数所处于的最佳范围。     

由Signless Laplacian谱确定的一类奇单圈图

为了探讨一类奇单圈图的Signless Laplacian谱惟一的的问题,利用图与其线图之间的关系,图与其多项系数之间的关系以及图与其同谱图之间的关系,证明了Signless Laplacian同谱图的一个重要的的结构,即:恰含一个奇单圈图的Signless Laplacian同谱图也是一个连通奇单圈图。在此基础上证明了一类奇单圈图的Signless Laplacian谱惟一性,确定了此类奇单圈图的结构。     

Stochastic Models for Multistage Cell Classification Systems

Probabilistic models for multistage cell classification systems are described. A simple finite Markov chain models classification events which occur as a cell passes through the system. The state space consists of various identities assigned to the cell, including true celi type and identities assigned by classifiers. Effects of throughput rate, data buffer capacity, and classifier processing rate on system performance are predicted by another model composed of a network of single server queues. Markov and queue models are interrelated in that classification events at one processor (modeled by the Markov chain) govern arrival rates of other processors. In turn, the queue model predicts the probability that a cell wili be missed due to fmite data buffer capacity. The miss event is modeled by the Markov chain as a possible classification outcome. Application of the models is illustrated for a multistage gynecologic flow prescreening system with slit-scan processing in the first stage and two dimensional image processing in the second. Results predict system sensitivity as a function of first stage false alann rate and abnormal cell occurrence rate.     

Statistical modeling of reliability in logic devices

Due to continuous technology scaling VLSI circuits feature an increasing susceptibility to transient faults. While complete elimination of errors cannot be guaranteed, current mitigation techniques based on circuit improvement or architectural measures cause a large overhead in terms of area and energy consumption. A more efficient possibility to cope with transient faults can be to tolerate hardware errors at low physical levels and handle them at higher system levels. This can be achieved by reusing error handling capabilities – such as channel decoders – or introducing specialized error correction blocks that take advantage of the system characteristics by concentrating the effort on the components and bits most crucial for system operation. To enable this approach the influence of hardware errors on system performance needs to be evaluated, requiring spatial and temporal models of error propagation in the system. Since Monte Carlo simulation of complex systems is not feasible, a statistical modeling technique of logic gates and circuits is introduced. This approach allows modeling of noise and variability influences on logic gates as well as correlation due to reconvergent fan-out with an error of 5% compared to Monte Carlo simulation but with considerably less runtime.     

Simulation of burst error models and an adaptive error controlscheme for high speed data transmission over analog cellularsystems

To realize high-speed data communication in a cellular system, the characteristics of mobile radio propagation paths (MRPP) and a robust error control scheme for poor circuit quality are studied. MRPP are analyzed by computer simulation, and an analysis method is described that uses a Markov model for burst errors generated by the simulation. By simulating the locus of moving vehicles, the relationship between the carrier-to-noise ratio (CNR), the fading frequency of a moving vehicle, and the three-states Markov model is obtained. An adaptive error control scheme (AECS) is developed as an effective high-speed data communication scheme in an analog cellular system. The effectiveness of the AECS is analyzed by simulating its application in a subcarrier transmission system with a 4800 b/s data transmission rate, using the three-states Markov model. The analysis method is verified and the characteristics of the AECS are evaluated using field data     

超宽带冲激脉冲正交解调接收机系统反射校正算法及其实现

基于超宽带冲激脉冲的信号特征,提出了超宽带正交解调接收机系统中脉冲信号的反射模型与校正算法。通过时域瞬态传输线模型、信号流图模型分析,指出整个系统可等效为一个延时滤波网络。最后提出了拟合该等效延时滤波网络,求解其补偿网络的具体校正算法。在实际系统目标探测的外场试验中,也验证了模型分析与校正算法的正确性和有效性。     

An importance sampling analysis of a noninterleaved Viterbi decoderin an RFI environment

This paper presents an importance sampling simulation model which analyzes a communications system consisting of a noisy channel, a transmitter/receiver, and a convolutional encoder/Viterbi decoder. The model determines the amount of signal degradation caused by any noise environment that can be modeled as a Markov chain. The specific example of a Radio Frequency Interference (RFI) noise environment is discussed in detail. The model uses importance sampling to determine low bit error rates (BERs) for a wide range of noise environments. It is faster than a conventional simulation because the required run time is independent of the BER. It is more flexible than existing analytic models, as these make major assumptions, such as that symbol errors are independent (interleaving), or that all bursts have infinite power. The model increases the simulation efficiency by biasing the channel statistics so that more codeword errors occur and adjusts for this by using a weighting function whose value is calculated through the use of a Markov chain. The results show that using interleaving results in a significant performance improvement when the lengths of the interfering bursts are long relative to the data symbol length     

Decomposition in Reliability Analysis of Fault-Tolerant Systems

Two important problems which arise in modeling fault-tolerant systems with ultra-high reliability requirements are discussed. 1) Any analytic model of such a system has a large number of states, making the solution computationally intractable. This leads to the need for decomposition techniques. 2) The common assumption of exponential holding times in the states is intolerable while modeling such systems. Approaches to solving this problem are reviewed. A major notion described in the attempt to deal with reliability models with a large number of states is that of behavioral decomposition followed by aggregation. Models of the fault-handling processes are either semi-Markov or simulative in nature, thus removing the usual restrictions of exponential holding times within the coverage model. The aggregate fault-occurrence model is a non-homogeneous Markov chain, thus allowing the times to failure to possess Weibull-like distributions. There are several potential sources of error in this approach to reliability modeling. The decomposition/aggregation process involves the error in estimating the transition parameters. The numerical integration involves discretization and round-off errors. Analysis of these errors and questions of sensitivity of the output (R(t)) to the inputs (failure rates and recovery model parameters) and to the initial system state acquire extreme importance when dealing with ultra-high reliability requirements.     

An ARQ mechanism considering resource and traffic priorities in cognitive radio systems

In multi-hop relaying systems that have many relay stations (RSs), a cognitive radio (CR) technique can improve system performance greatly, due to an efficient resource sharing between the RSs. In this letter, the performance of an ARQ mechanism for CR-based multi-hop relaying systems is studied, using Markov chain and matrix signal flow graph (MSFG) techniques. Also, a priority-based resource allocation scheme is proposed to prevent performance degradation caused by the usage of unstable resources acquired by the CR technique.     

Saturation throughput analysis of IEEE 802.11 in the presence of non ideal transmission channel and capture effects

In this paper, we provide a saturation throughput analysis of the IEEE 802.11 protocol at the data link layer by including the impact of both transmission channel and capture effects in Rayleigh fading environment. Impacts of both non-ideal channel and capture effects, specially in an environment of high interference, become important in terms of the actual observed throughput. As far as the 4-way handshaking mechanism is concerned, we extend the multi-dimensional Markovian state transition model characterizing the behavior at the MAC layer by including transmission states that account for packet transmission failures due to errors caused by propagation through the channel. This way, any channel model characterizing the physical transmission medium can be accommodated, including AWGN and fading channels. We also extend the Markov model in order to consider the behavior of the contention window when employing the basic 2-way handshaking mechanism. Under the usual assumptions regarding the traffic generated per node and independence of packet collisions, we solve for the stationary probabilities of the Markov chain and develop expressions for the saturation throughput as a function of the number of terminals, packet sizes, raw channel error rates, capture probability, and other key system parameters. The theoretical derivations are then compared to simulation results confirming the effectiveness of the proposed models.     

Effects of redundancy management on reliability modeling

Two methods are investigated for incorporating the effects of fault detection and isolation (FDI) decision errors and redundancy management (RM) policy into reliability models for a simple single-component-dual-redundant system. These two methods are combinatorial analysis and Markov chain modeling. Reliability analysts have traditionally chosen the classical combinatorial approach. However, the authors show that the existence of time-ordered event sequences resulting from the interaction of FDI decision errors with the RM policy considerably complicates the construction of the combinatorial model. An error analysis illustrates that a simplified combinatorial model, which ignores these time-ordered event sequences, inaccurately predicts the system reliability. The Markov modeling technique is an excellent alternative to the combinatorial approach because it easily and accurately accounts for time-ordered event sequences such as those present in fault-tolerant systems     

一种求解最小割的警示传播算法

最小割问题（minimum cut problem）是NP（Non-deterministic Polynomial）难问题,警示传播算法（warning propagation）是一种基于因子图的消息传递算法,可用于求解组合优化问题.首先,本文借助隐马尔可夫模型将无向图转换为因子图,将求解最小割映射为求解因子图的相应问题.进而设计一种求解最小割的警示传播算法.最后,选取了几组随机无向图实例进行数值实验,实验结果表明,该算法在求解速度上优于同类算法.     

Resource management model and performance evaluation for satellite communications

Efficient resource management is mandatory to achieve maximum system capacity for next generation communications systems. Resource management deals with the available spectral band, time, power, and space for a transmission signal. It includes (i) the frequency planning, (ii) the selection of transmit power, and (iii) the assignment of the channels and access nodes to the users. The paper presents a generalized notation as well as graph algorithms for resource management problems. Impairment graphs can be used for frequency planning, whereas flow graphs are suitable for channel access problems. To evaluate the performance of the resource management, service criteria (such as blocking or the carrier to interference ratio C/I) or efficiency criteria (bandwidth requirements) can be derived from the graphs. The resource management techniques are applied to satellite networks with non‐geostationary orbits yielding time‐variant network topologies. As a simple example, the channel assignment and capacity optimization of the EuroSky Way system are shown. Furthermore, a comparison of fixed, dynamic and hybrid channel allocation schemes (FCA, DCA, HCA) for a typical MEO satellite scenario is given. Satellite diversity and its impact on bandwidth requirement and transmission quality is also examined. Finally, it is shown how spread spectrum systems can be investigated with the presented tools. Copyright © 2001 John Wiley & Sons, Ltd.     

Analysis of an integrated voice and data transmission system usingpacket reservation multiple access

Packet reservation multiple access (PRMA) is a channel access protocol proposed for the third generation wireless information networks which have attracted considerable attentions recently. By using the equilibrium point analysis (EPA), a PRMA integrated voice and data system has been studied in previous research. However, the error between numerical results of the analysis and those of simulation is relatively large. In this paper, we also study an integrated voice and data system with PRMA. The system performance is evaluated by using a Markov analysis method. First, some analytic models are constructed such that the system transition can be described by a Markov chain. Then, we calculate the entries of the one step state transition matrix using an iterative procedure. Finally, system performance measures, such as throughput and delay, are evaluated. Little error between numerical results of analysis and those of simulation indicates that the method is appropriate to analyze PRMA systems,