基于连接两段激活模型的IEEE 802.16接纳控制算法

IEEE802.16系统中数据的传输是面向连接的,连接的建立服从两段激活模型。针对系统空闲资源耗尽但还为已接纳而未被激活的业务预留资源这一情况,该文提出了一种适当借用此预留资源去接纳新的立即被激活业务的接纳控制算法,并建立了此算法的3维马尔可夫链模型,进行了理论分析提出了找寻此算法中使用的两个门限的搜索方法。仿真结果表明,该接纳控制算法能显著地降低新业务阻塞率,提高系统的带宽利用率,已接纳业务的激活成功率只有少许下降。     

基于能效优化的WSNs多径流量分配路由算法

该文针对传感器节点能量受限的特点建立能效优化模型,该模型兼顾网络传输能耗和能耗均衡特性,以最大化网络节点总剩余能量和最小化剩余能量的方差为目标,通过合理分配多条路径的流量来优化网络能效。利用权衡评价函数实现了模型的求解,进而提出一种多径流量分配路由(MFAR)算法。仿真实验表明,该算法能够合理配置各路径流量,显著提高网络能量效率,达到在降低网络能耗的同时保证能耗分布均衡的目标。     

改进的最大后验概率估计法实现单幅图像超分辨率重建

从图像降质模型出发,研究运用最大后验概率(MAP)估计法实现图像超分辨率重建。简单介绍了MAP方法的发展现状,并分析了该算法中存在的缺陷,即目标函数的吉布斯(Gibbs)项对于重建图像的噪声抑制力不均衡。针对该缺陷采用原始低分辨率图像插值后图像的梯度场对MAP目标函数的Gibbs项系数进行修正,使该系数对各像素根据相应梯度值自适应的调整,在一定程度上均衡了目标函数对于不同梯度值区域的约束力。采用共轭梯度法对改进前后MAP算法分别求解并进行了仿真。结果显示相比传统MAP算法,改进的MAP算法得到的超分辨率图像,既很好地恢复了细节,又很好地抑制了重建过程中引入的噪声,总体像质有了明显提高,同时在迭代求解过程中也表现出很好的收敛性与稳定性。     

无线局域网室外覆盖路径损耗计算分析及规划布局建议

介绍了无线局域网(WLAN)所用IEEE 802.11x标准的技术特点和频率特性,选择修正的COST231 HATA无线信号传播模型对信号路径损耗进行计算,以图表的形式描述了WLAN所在频段(2.4 G-Hz)的空间信道衰落特征.通过计算得出结论:随着传输距离和AP/STA天线高度差的增加,WLAN无线信道路径损耗将迅...     

Assignment of inter-die signals in a simplified wiring model for die-stacking SiP designs

Compared with traditional flow in IC designs, the assignment of the inter-die signals between different dies is an important stage in a die-stacking SiP design. In this paper, given a tolerant spacing rule between two inter-die signals, the crossing constraint between two inter-die signals can be firstly defined for the bonding wires in a die-stacking SiP design with a simplified wiring model [7]. Furthermore, based on the connection constraint on any inter-die signal, the capacity constraint on any assigned pad on dies and the crossing constraint between two inter-die signals, an integer linear programming-based (ILP-based) approach is proposed to assign all the inter-die signals to minimize the total wirelength in a die-stacking SiP design. Compared with Lin’s two-stage approach [4] for some tested examples without a tolerant spacing distance between two inter-die signals in an Euclidean wiring model, the experimental results show that our proposed ILP-based approach increases 4.5% of CPU time and reduces 6.2% of total wirelength to assign all the inter-die signals on the average. Besides that, compared with Yan’s iterative approach [6] for some tested examples without a tolerant spacing distance between two inter-die signals in an Euclidean wiring model, the experimental results show that our proposed ILP-based approach uses reasonable CPU time to reduce 5.3% of total wirelength to assign all the inter-die signals on the average. Compared with Lin’s modified two-stage approach and Yan’s modified iterative approach for some dense tested examples with a tolerant spacing distance between two inter-die signals in a simplified wiring model [7], the experimental results show that Lin’s modified two-stage approach only achieves 95.9% of the assignment ratio on the average, Yan’s modified iterative approach only achieves 96.6% of the assignment ratio on the average and our proposed ILP-based approach uses reasonable CPU time to achieve 100% of the assignment ratio.     

A human visual system-driven image segmentation algorithm

This paper presents a novel image segmentation algorithm driven by human visual system (HVS) properties. Segmentation quality metrics, based on perceptual properties of HVS with respect to segmentation, are integrated into an energy function. The energy function encodes the HVS properties from both region-based and boundary-based perspectives, where the just-noticeable difference (JND) model is employed when calculating the difference between the image contents. Extensive experiments are carried out to compare the performances of three variations of the presented algorithm and several representative segmentation and clustering algorithms available in the literature. The results show superior performance of our approach.     

Wavelet-based hybrid natural image modeling using generalized Gaussian and α-stable distributions

Natural image is characterized by its highly kurtotic and heavy-tailed distribution in wavelet domain. These typical non-Gaussian statistics are commonly described by generalized Gaussian density (GGD) or α-stable distribution. However, each of the two models has its own deficiency to capture the variety and complexity of real world scenes. Considering the statistical properties of GGD and α-stable distributions respectively, in this paper we propose a hybrid statistical model of natural image’s wavelet coefficients which is better in describing the leptokurtosis and heavy tails simultaneously. Based on a clever fusion of GGD and α-stable functions, we establish the optimal parametric hybrid model, and a close-formed Kullback–Leibler divergence of the hybrid model is derived for evaluating model accuracy. Experiment results and comparative studies demonstrate that the proposed hybrid model is closer to the true distribution of natural image’s wavelet coefficients than the single modeling using GGD or α-stable, while is beneficial for applications such as image comparison.     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.     

An analytical model for optimizing the performance of graphene based silicon Schottky barrier solar cells

In this paper, a model taking into account the effects of carrier loss mechanisms has been developed. The model simulates the photovoltaic properties of the graphene/n-type silicon Schottky barrier solar cells (G/n-Si_SBSC), and it can reproduce the experimentally determined parameters of the G/n-Si_SBSC. To overcome the low efficiencies of G/n-Si_SBSC, their performances have been optimized by modifying the work function of graphene and Si properties, accounted for variation of its thickness and doping level. The obtained results show that the work function of graphene has the major impact on the device performance. Also, the temperature dependence of the G/n-Si_SBSC performance is investigated.     

AR模型功率谱估计在抗干扰中的DSP实现

本文在AR模型(自回归模型)功率谱估计方法的基础上,对其在抗干扰领域中的应用进行了研究,提出了自适应滤除干扰信号的方案,并对该方案进行了DSP实现。实验结果表明,该方案在自适应去除多个干扰信号方面是行之有效的。