Periodicity of Two-Dimensional Bonding of Main Group Elements

In the periodic table the position of each atom follows the ‘aufbau’ principle of the individual electron shells. The resulting intrinsic periodicity of atomic properties determines the overall behavior of atoms in two-dimensional (2D) bonding and structure formation. Insight into the type and strength of bonding is the key in the discovery of innovative 2D materials. The primary features of 2D bonding and the ensuing monolayer structures of the main-group II–VI elements result from the number of valence electrons and the change of atom size, which determine the type of hybridization. The results reveal the tight connection between strength of bonding and bond length in 2D networks. The predictive power of the periodic table reveals general rules of bonding, the bonding-structure relationship, and allows an assessment of published data of 2D materials.     

A signal adaptive diffusion filter for video coding: Mathematical framework and complexity reductions

In this paper we combine video compression and modern image processing methods. We construct novel iterative filter methods for prediction signals based on Partial Differential Equation (PDE) based methods. The mathematical framework of the employed diffusion filter class is given and some desirable properties are stated. In particular, two types of diffusion filters are constructed: a uniform diffusion filter using a fixed filter mask and a signal adaptive diffusion filter that incorporates the structures of the underlying prediction signal. The latter has the advantage of not attenuating existing edges while the uniform filter is less complex. The filters are embedded into a software based on HEVC with additional QTBT (Quadtree plus Binary Tree) and MTT (Multi-Type-Tree) block structure. In this setting, several measures to reduce the coding complexity of the tool are introduced, discussed and tested thoroughly. The coding complexity is reduced by up to 70% while maintaining over 80% of the gain. Overall, the diffusion filter method achieves average bitrate savings of 2.27% for Random Access having an average encoder runtime complexity of 119% and 117% decoder runtime complexity. For individual test sequences, results of 7.36% for Random Access are accomplished.     

On the effects of the packet size distribution on the packet loss process

Real-time multimedia applications have to use forward error correction (FEC) anderror concealment techniques to cope with losses in today’s best-effort Internet. The efficiency of these solutions is known however to depend on the correlation between losses in the media stream. In this paper we investigate how the packet size distribution affects the packet loss process, that is, the distribution of the number of lost packets in a block, the related FEC performance and the average loss run length. We present mathematical models for the loss process of the MMPP+M/D/1/K and the MMPP+M/M/1/K queues; we validate the models via simulations, and compare the results to simulation results with an MPEG-4 coded video trace. We conclude that the deterministic packet size distribution (PSD) not only results in lower stationary loss probability than the exponential one, but also gives a less correlated loss process, both at a particular average link load and at a particular stationary loss probability as seen by the media stream.Our results show that for applications that can only measure the packet loss probability, the effects of the PSD on FEC performance are higher in access networks, where a single multimedia stream might affect the multiplexing behavior. Our results show that the effects of the PSD on FEC performance are higher in access networks, where a single multimedia stream might affect the multiplexing behavior and thus can improve the queuing performance by decreasing the variance of its PSD.     

基于矢量平均的信道估计算法

提出一种适用于DS-CDMA无线通信系统的低计算量而性能良好的信道估计算法。在DS-CDMA系统中，当接收信号经过解扩或多用户检测等时域预处理后，可以认为干扰大大减弱、期望信号在处理后的信号中占主要地位。这样，用预处理后信号相关阵的最大特征值对应的特征矢量可以很好地近似期望信号的信道矢量。但是，直接特征分解需要很大的计算量，特征跟踪计算量较低，但瞬态性能较差。本文提出一种基于相关矩阵列矢量平均的信道估计算法，该算法不需要特征分解或跟踪。仿真结果表明：新算法在降低计算量的情况下可以获得同直接特征分解方法几乎相同的性能。     

具有控制项的限定记忆卡尔曼滤波器

在已有的限定记忆卡尔曼滤波器的基础上 ,将确定性先验信息作为控制项加以应用 ,推导出了完整的限定记忆卡尔曼滤波公式 ,从而在记忆长度确定的情况下 ,有效地减小了模型不准的误差 ,降低了滤波总误差。仿真同样表明了该方法的有效性     

Analysis on X-Ray Laser Generation with EM-Wave Wiggler

The possibility of realizing SASE Free Election Laser in x-ray waveband with EM-wave wiggler is studied in this paper. SASE effect including saturation length, saturation power and nonlinear process is explored through a 3-D simulation code. A utilization of seed light from laser plasma x-ray is also analyzed, which demonstrates the feature of shortening the interaction length for saturation. The results show that sizeable output power of x-ray laser would be generated with a middle energy electron beam.     

用于提高国产氩离子激光器相干长度的相干扩展器

本文报导了最近研制成功的用于提高国产氩离子激光器相干长度的相干扩展器。利用这种基于F-P理论的相干扩展器可以使国产氩离子激光器的相干长度由不足5cm一下提高到m的量级,功率损耗在25%～40%之间,有着很好的应用前景。     

Kalman filtering of a space-time Markov random field

In this paper, finite-dimensional recursive filters for space-time Markov random fields are derived. These filters can be used with the expectation maximization (EM) algorithm to yield maximum likelihood estimates of the parameters of the model.     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at