面向PKCS的大数模运算算法的测试与分析

本文比较分析了两种面向ＰＫＣＳ的快速模运算算法－单表制算法和双表制算法，给出了这两种算法的时空复杂性，鉴于实用考虑，本项研究着重对两个算法进行了对比测试。结果表明，双表制算法较单表制算法提高效率３０％～５０％，同时双表制算法以递推方式建立预计算表提高了预计算效率１８０％～４９０％，为公钥动态管理提供便利，此外，本文以大数运算在ＲＳＡ中的应用为例，比较了分析出采用双表制算法加／解密模运算过程较单表制     

模为合数时多值模代数的模减与模除运算

本文提出并分析了模为合数时多值逻辑中模加与模乘运算的逆运算－模减与模除运算。它的引入使模减，模除运算的基数（模）的取值域从素数扩展到合数，从而完善了对模代数中的模减、模除运算的研究。     

面向PKCS的快速模运算算法

本文根据PKCS(Public Key Cryptosystem)中大数运算的特点,提出了一套模运算的双表算法,并基于数论理论,就该算法的基础及其复杂性给出了完善的证明。整套算法的基本思想是:以空间换取时间。其建预表的递推方法大大地提高了建表效率,并且两个表都直接参与模运算,显著地提高了运算效率。     

大数模幂乘运算的VLSI实现

信息加密,数字答乐,身份证等等是信息安全领域的重要内容,只有公钥密友体制才能很好地解决这些问题,大数模幂乘运算是许多公钥密友体制的核心运算,也是运算效率提高的瓶颈。基于Ｍｏｎｔｇｏｍｅｒｙ模乘变换,构造了一种新型的脉动阵列架构模乘运算器。结合简单二进制幂运算算法,采用０．８μｍ ＣＭＯＳ工艺,成功地设计并制造了２５６ｂｉｔ模幂乘运算器ＴＨＭ２５６,电路规模为１８６７７门,芯片面积为１７．６３ｍｍ６     

一种自适应的关键帧选取算法

文章针对传统的视频编码方法中,当预测图像中绝大多数图像块在参考帧中都找不到相似的块时,其预测效果急剧降低的问题,在对具有预测关系的视频图像集进行分析计算的基础上,设计了一种动态选择关键帧的算法.实验结果表明,该方法能有效地提高视频图像的压缩率.     

长整数模运算的体系结构研究与实现

随着计算机网络技术的迅猛发展和网络技术在各行各业中的广泛应用,信息安全问题日益突出.密码技术可以有效的保证信息的保密性、完整性、可用性和抗抵赖性.密码技术,特别是公钥密码技术中的RSA算法和椭圆曲线(Ellipse Curve Cryptography, ECC)算法的硬件电路级实现,代表着一个国家信息安全保障的水平.主要研究工作为长整数模运算的体系结构研究与实现.对几种模乘运算算法进行研究,并对线性和高基两种电路体系结构进行比较.     

一种新的自适应偏振模色散补偿前馈方法

提出了一种新偏振模色散（PMD）补偿的方法，直接从被补偿光纤中提取偏振色散矢量的大小和方向信息，根据算法调节偏振模色散补偿器的各参量，使得补偿器的快轴与被补偿光纤的慢轴对准，从而使得偏振模色散得到补偿。这种方法的优点是减少了搜索的自由度。建立了40Gb／s偏振模色散前馈补偿系统，并通过数值模拟．对40Gb／s的非归零（NRZ）码的偏振模色散进行了自适应补偿。通过对补偿前后的眼图、偏振度（DOP）和Q值进行对比和分析，结果表明，这种偏振模色散补偿的前馈方法是非常有效的。     

多机被动定位协同平台自适应选取研究

针对多机测角被动定位精度提升问题,提出了一种低速数据链条件下载机运动无约束的协同平台自适应选取方法。在算法实现中,首先推导了一种基于圆概率误差的协同平台自适应选取函数,并给出了两平台自适应选取函数的具体公式,其次给出了协同平台自适应选取设计方法,最后是节点选取的求解方法。仿真结果表明,所提出的算法能够实时地根据敌我位置相对几何关系,动态选取参与目标位置解算的协同平台,大大提高了多机被动定位系统的定位精度。     

电源自适应Rail-to-Rail CMOS运算放大器

基于CSMC 0.6 μm标准CMOS工艺,实现了一种电源自适应Rail-to-Rail CMOS运算放大器,其输入级从原理上变“被动地“适应低电压为“主动地“要求低电压.当外部电源电压在2.1V到3.2 V变化时,内部电源电压稳定在1.68 V,最大偏差为5.4%.这样,内部电源电压自适应地稳定在“相交条件“,实现了输入级的跨导Gm为常数:在整个共模(CM)电压变化范围内,输入级跨导的最大变化为9%.Rail-to-rail输出级用两个折叠网格和AB类反馈控制结构实现,使输出级的最低电源电压降到Vgs 2Vds,并使输出静态电流最小.     

模幂运算的并行算法NSP

给出一种基于预处理计算的模幂运算并行算法NSP,在并行数据分布、并行运行方式等方面较以往的并行算法有更大的灵活性,在曙光-2000上进行了模拟实验,结果表明,由于平方-乘的运算量很少,该并行算法大大节约了模幂运算的时间。     

An adaptive multiresolution approach to the simulation of planarstructures

An efficient approach for the full-wave analysis of printed structures is presented. It is based on the use of vector multiresolution (MR) functions in conjunction with the impedance matrix compression (IMC) technique, which leads to a reduced set of iteratively selected basis functions. The multilevel structure of the functions makes the matrix compression possible and also allows its further sparsification, with the subsequent reduction of the computational time and the matrix memory occupancy. Numerical results confirm the efficiency of the technique     

Fuzzy-set approach to select maintenance strategies for multistateequipment

Maintenance of any equipment based on its condition is unavoidable. The condition of the equipment can be represented using fuzzy sets. This paper details a fuzzy-set model for maintenance policy of multistate equipment; the model is based on: (a) equipment condition and remaining life, and (b) maximizing a known detailed utility function. The model is extended to maintenance planning for the entire life of the equipment. The results are useful for replacement decisions as well as for inventory control     

An adaptive approach to suppress powerful impulsive interference

In this paper the problem of impulsive noise suppression by using adaptive prediction technique is considered. The Time Domain Notch Filter structure and a procedure to estimate the filter coefficients are proposed. The considered algorithm is linear and does not require any auxiliary reference input. Performance evaluation indicates that the use of this algorithm does not change the signal-to-noise ratio (SNR) whose value remains almost independent of impulsive interference power. On the other hand, the signal-to-impulsive interference ratio (SIR) in the output increases with a decrease in the input SIR. This property of the proposed algorithm is the most essential difference between it and the commonly employed algorithms. The results of computer simulation of a noncoherent detection system applied to the on-off-keying modulation are given. The obtained results confirm that the proposed algorithm enables a transmission in the background of high power impulsive interference.     

An alternative approach to linearly constrained adaptive beamforming

A beamforming structure is presented which can be used to implement a wide variety of linearly constrained adaptive array processors. The structure is designed for use with arrays which have been time-delay steered such that the desired signal of interest appears approximately in phase at the steered outputs. One major advantage of the new structure is the constraints can be implemented using simple hardware differencing amplifiers. The structure is shown to incorporate algorithms which have been suggested previously for use in adaptive beamforming as well as to include new approaches. It is also particularly useful for studying the effects of steering errors on array performance. Numerical examples illustrating the performance of the structure are presented.     

An adaptive approach to the numerical solution of Fresnel's waveequation

An adaptive approach to the numerical solution of the wave propagation in integrated optics devices with 1-D cross sections is described. Fresnel's approximation of the exact wave equation resulting from Maxwell's equations is considered. A criterion to estimate the validity of this approximation is derived. Discretization in longitudinal direction with step-size control leads to a stationary subproblem for the transversal field distribution, which is then handled by an adaptive finite-element method. Thus, full adaptivity of the algorithm is realized. The numerical examples focus on waveguide tapers     

An adaptive KPCA approach for detecting LDoS attack

Low‐rate denial‐of‐service (LDoS) attack sends out attack packets at low‐average rate of traffic flow in short time. It is stealthier than traditional DoS attack, which makes detection of LDoS extremely difficult. In this paper, an adaptive kernel principal component analysis method is proposed for LDoS attack detection. The network traffic flow is extracted through wavelet multi‐scale analysis. An adaptive kernel principal component analysis method is adopted to detect LDoS attack through the squared prediction error statistics. Key parameters such as the parameter of the radial basis function, the number of principal components, and the squared prediction error confidence limit are adaptively trained with training data and updated with the network environment. Simulation is accomplished in NS‐2 environment, and results prove the favorable LDoS attack detection efficiency by the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd.     

An adaptive approach for designing phase compensation filters

The objective of this communication is to introduce an adaptive method for designing filters to compensate for nonlinear phase shift introduced into a data stream by fixed (i.e., nonadaptive) recursive digital filters, e.g., those obtained via the bilinear transform.     

An adaptive approach for the identification of improper complex signals

A real-time approach for the identification of second-order noncircularity (improperness) of complex valued signals is introduced. This is achieved based on a convex combination of a standard and widely linear complex adaptive filter, trained by the corresponding complex least mean square (CLMS) and augmented CLMS (ACLMS) algorithms. By providing a rigorous account of widely linear autoregressive modelling the analysis shows that the monitoring of the evolution of the adaptive convex mixing parameter within this structure makes it possible to both detect and track the complex improperness in real time, unlike current methods which are block based and static. The existence and uniqueness of the solution are illustrated through the analysis of the convergence of the convex mixing parameter. The analysis is supported by simulations on representative datasets, for a range of both proper and improper inputs.     

An adaptive clustering approach for the management of dynamic systems

Adaptive clustering is one of the fundamental problems behind autonomic systems and, more generally, an open research issue in the area of networking and distributed systems. The problem of giving structure to large-scale, dynamic systems through clustering and of electing centrally located nodes (cluster heads) is nontrivial. This is in fact an NP-complete problem when striving for optimality. We propose an innovative strategy based on code mobility that dynamically computes near-optimal clusters in linear time. Our approach is autonomic, does not require any user intervention, is self-configuring, self-optimal, and self-healing. We demonstrate these features through an extensive set of simulations, discussing the viability of the algorithm based on state-of-the art technologies, and elaborating on its applicability to distributed monitoring, peer-to-peer systems, application-level multicast, and content adaptation networks.