Analysis of distribution time of multiple files in a P2P network

Peer-to-Peer (P2P) file sharing attracts much attention due to its scalability and robustness. One important metric in measuring the performance of a P2P file sharing system is the amount of time required for all peers to get the files. We refer this time as the file distribution time. Researchers have proposed protocols to minimize the file distribution time under different situation. However, most works are based on the single-file scenario. On the other hand, there are studies showing that in a file sharing application, users may download multiple files at the same time. In this paper, we analyze the minimum time needed to distribute multiple files. We develop an explicit expression for the minimum amount of time needed to distribute multiple files in a heterogeneous P2P fluid model. Unlike the single-file scenario, we demonstrate that the theoretical lower bound in multi-file is not always achievable. With a comprehensive consideration of all the configurations, we elaborate how to partition the bandwidth capacities of both seeds and leechers for a particular file such that the finish time is optimal.     

Adaptive Decentralized NN Control of Nonlinear Interconnected Time‐Delay Systems with Input Saturation

In this paper, a novel decentralized adaptive neural control scheme is proposed for a class of interconnected large‐scale uncertain nonlinear time‐delay systems with input saturation. Radial basis function (RBF) neural networks (NNs) are used to tackle unknown nonlinear functions. Then, the decentralized adaptive NN tracking controller is constructed by combining Lyapunov–Krasovskii functions and the dynamic surface control (DSC) technique, along with the minimal‐learning‐parameters (MLP) algorithm. The stability analysis subject to the effect of input saturation constraints are conducted with the help of an auxiliary design system based on the Lyapunov–Krasovskii method. The proposed controller guarantees uniform ultimate boundedness (UUB) of all of the signals in the closed‐loop large‐scale system, while the tracking errors converge to a small neighborhood around the origin. An advantage of the proposed control scheme lies in the number of adaptive parameters of the whole system being reduced to one and in the solution of the three problems of “computational explosion,” “dimension curse,” and “controller singularity”. Finally, simulation results along with comparisons are presented to demonstrate the advantages, effectiveness, and performance of the proposed scheme.     

Stochastic computer network with multiple terminals under total accuracy rate

From the viewpoint of service level agreements,data transmission accuracy is one of the critical performances for assessing Internet by service providers and enterprise customers.The stochastic computer network(SCN),in which each edge has several capacities and the accuracy rate,has multiple terminals.This paper is aimed mainly to evaluate the system reliability for an SCN,where system reliability is the probability that the demand can be fulfilled under the total accuracy rate.A minimal capacity vector allows the system to transmit demand to each terminal under the total accuracy rate.This study proposes an efficient algorithm to find all minimal capacity vectors by minimal paths.The system reliability can then be computed in terms of all minimal capacity vectors by the recursive sum of disjoint products(RSDP) algorithm.     

采用2D-SMPC码的S-OCDMA系统性能分析

在同步修正素数码（SMPC）基础上,通过给每个不同的种子分配一个不同的波长片,构造了二维正交地址码（2D-SMPC）;分析了码字的相关特性,确定了地址码选取原则;通过Optisystem仿真,研究了该码的多址干扰（MAI）和系统容量等性能。与一维SMPC码性能相比较,验证了其用于S-OCDMA系统时的性能改善。     

基于Matlab与VC的弱视视功能检查系统的设计与实现

弱视是一种发育紊乱性疾病,我国弱视患者检出率高达2.8%。对弱视视功能进行检查可以帮助医生更准确判定病情,从而制定有效的个性化治疗方案。针对弱视患者存在的视功能缺损模式,采用心理物理学的阈限算法,设计了弱视视功能检查系统。系统软件部分利用VC中的MFC以及Matlab的Psychophysics Toolbox实现视功能检查模块,通过SQL Server建立后台数据库记录检查数据。同时,为了达到心理物理学上对视功能检查的特殊显示要求,硬件部分加入了Vedio Switcher进行输出视频信号的转换。系统经临床实际试用,表明系统稳定性好,能满足弱视视功能检查的特殊临床需要。     

论区间B样条曲线的升阶与割角的关系

为了解决区间B样条曲线的升阶理论问题,提出区间控制多边形概念,利用双次B样条基函数证明了区间B样条曲线具有升阶性质;并阐明了区间B样条曲线的升阶就是对其控制多边形的割角过程.最后证明了当升阶次数趋于无穷时,区间B样条曲线的控制多边形收敛到该曲线.     

基于径向基函数神经网络的红外步态识别

为提高红外步态识别的效果,提出一种基于径向基函数神经网络的多分类器融合算法。对红外步态序列,分别应用基于轮廓线傅立叶描述子特征的模糊分类器和基于下肢关节角度特征的贝叶斯分类器进行识别,再利用径向基函数神经网络的学习和分类功能,对获得的输出信息进行度量层的融合和再识别。仿真实验结果表明,该算法获得更加精确的分类效果。     

基于ActiveX控件及多线程的串行通信

详细介绍一个基于ActiveX控件和多线程的串行通信模块的设计方案,分析了串行通信中所要求的实时性、更高效率的执行时间、存储空间、较短开发周期和较高可靠性等各种因素,以面向对象的分析和设计为指导,实现了一个封装完整的、具有数据收发和协议处理功能的ActiveX控件,并实现基于多线程技术串行通信的方法。     

基于遗传算法的函数型小波网络

针对传统小波神经网络易陷入局部极小等缺陷,采用遗传算法对神经网络进行优化。提出了一种结合实数编码与二进制编码的多值编码遗传算法,上述算法在同一条染色体上同时使用实数编码与二进制编码,有机结合了两者的优点,并把遗传算法用于优化函数型小波网络的结构中,可获得具有更好泛化能力的小波网络。仿真实验结果表明,利用该遗传算法训练小波神经网络,能使网络具有简单的结构形式,较高的逼近精度和较强的泛化能力,并证实了网络的有效性和优越性能。     

Nth-order fuzzy linear differential equations

In this paper a numerical method for solving nth-order linear differential equations with fuzzy initial conditions is considered. The idea is based on the collocation method. The existence theorem of the fuzzy solution is considered. This method is illustrated by solving several examples.