Signal‐noise support vector model of a microwave transistor

In this work, a support vector machines (SVM) model for the small‐signal and noise behaviors of a microwave transistor is presented and compared with its artificial neural network (ANN) model. Convex optimization and generalization properties of SVM are applied to the black‐box modeling of a microwave transistor. It has been shown that SVM has a high potential of accurate and efficient device modeling. This is verified by giving a worked example as compared with ANN which is another commonly used modeling technique. It can be concluded that hereafter SVM modeling is a strongly competitive approach against ANN modeling. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2007.     

Efficient multi‐fidelity design optimization of microwave filters using adjoint sensitivity

A simple and robust algorithm for computationally efficient design optimization of microwave filters is presented. Our approach exploits a trust‐region (TR)‐based algorithm that utilizes linear approximation of the filter response obtained using adjoint sensitivity. The algorithm is sequentially executed on a family of electromagnetic (EM)‐simulated models of different fidelities, starting from a coarse‐discretization one, and ending at the original, high‐fidelity filter model to be optimized. Switching between the models is determined using suitably defined convergence criteria. This arrangement allows for substantial cost reduction of the initial stages of the optimization process without compromising the accuracy and resolution of the final design. The performance of our technique is illustrated through the design of a fifth‐order waveguide filter and a coupled iris waveguide filter. We also demonstrate that the multi‐fidelity approach allows for considerable computational savings compared to TR‐based optimization of the high‐fidelity EM model (also utilizing adjoint sensitivity). © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:178–183, 2015.     

EM‐based yield optimization exploiting trust‐region optimization and space mapping technology

Design centering is a design problem which looks for nominal values of circuit parameters that maximize the probability of satisfying the design specification (yield function). Direct yield optimization of electromagnetic (EM)‐based circuits is obstructed by the high expense of EM simulations required in the yield estimation process. Also, the absence of any gradient information represents an obstacle against the optimization process. In this article, a new approach for design centering and yield optimization of EM‐based circuits is introduced. In the proposed approach, the generalized space mapping (SM) technique is incorporated with a derivative‐free trust region optimization method (NEWUOA). Moreover, a variance reduction sampling technique is implemented in the yield estimation process. Two techniques suitable for the microwave circuit design centering process are introduced. The first technique exploits the surrogate developed using any circuit optimizer, for example, minimax optimizer, in the yield maximization process. While the second technique iteratively constructs and updates an SM surrogate during the yield optimization process. Our novel approach is illustrated by practical examples showing its efficiency. One of the examples is entirely designed within the sonnet em environment. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:474–484, 2015.     

Reliable design optimization of microwave structures using multipoint‐response‐correction space mapping and trust regions

Space mapping (SM) is one of the most efficient simulation‐driven design technologies used in microwave engineering to date. It includes so‐called output SM that ensures exact matching between the EM‐evaluated microwave structure under consideration (fine model) and its surrogate at the current design. The standard, single‐point output SM exploits the fine model data at a single design and is not able to align the models' sensitivity. Here, a multipoint response correction is proposed that generalizes the concept of output SM. By using a design‐variable‐dependent correction term and exploiting all available fine model information, the proposed technique provides exact match between the surrogate and the fine model at several designs. This retains the benefits of output SM but also enhances sensitivity matching between the two models, which results in improved performance of the SM optimization process. The efficiency of the propose approach is demonstrated using several microwave design problems. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2011.     

Printed dipole antenna design using artificial neural network modeling for RFID application

An approach to printed dipole antenna design using the artificial neural network (ANN) modeling technique is presented in this article. Three important antenna‐layout dimensions are used to capture critical input/output relationships in the ANN model. Once fully developed, the ANN model has been shown to be as accurate as an EM simulator and much more efficient computationally in antenna design optimization. © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2006.     

改进的PKI可信度模型

为提高证书依赖方(Relying Party)对证书持有者(Subscriber)信任评价的准确度,提出一种改进的PKI可信度模型.通过引入密钥安全期和优化不可信因子,严格区分证书可信度和私钥可信度,提出对应的计算公式,并给出组合密钥可信度和平均密钥可信度的计算方法.针对单级CA信任模型,推导出平均证书可信度和平均私钥可信度.该模型将影响密钥可信度的多个关键因素统一体现在单个计算公式中,不仅能够适应多种PKI信任模型,同时为提高证书持有者信任评价的准确度提供计算依据.     

PKI中桥信任模型的优化

PKI中存在多个可信任点和无终止的可信任环的可能性,使证书认证路径的有效发现复杂和耗时,路径构造的任务非常繁重。提出的基于路径代理的桥信任模型利用路径代理服务器,采用生成树算法提前进行路径构造存储,从而将复杂的路径构造问题转化为路径查询问题,实现了对PKI桥信任模型的优化。     

一种新的PKI信任度模型算法设计

PKI体制中的信任机制存在缺陷,分析了信任的特性以及目前PKI体制中实体间信任的缺陷;信任度机制能够缓解PKI中的信堡苎机。对Beth信任度算法进行了研究,分析了其存在的缺陷,并提出了新的信任度模型算法,新算法利用概率统计理论放松了对直接信任的限制,通过惩罚系数以及位置参数解决了惩罚不均的现象,利用最可靠路径的BRP算法得到了系统中总体最可靠信任的路径,避免了,推荐信任中的不稳定,并提高了认证的效率和准确性。     

PKI安全信任模型的研究

公钥基础设施(PKI)为电子商务提供了一个安全平台,而其信任模型的确定是实施PKI系统的关键开始步骤,文中对目前常用的信任模型进行了分析,提出了一种新的混合信任模型,在该模型中引入了路径服务器来完成信任路径的构建,并对实现中的一些关键技术问题提出了解决方法.     

一种PKI信任模型逻辑推理的改进方法

为了简化PKI信任模型的逻辑推理,本文对Bakkali H E和他dtouni B I提出的两种推理方法进行了改进。首先通过使用三个谓词和三个约束条件给出与信任模型相关的定义和推理规则,并在此基础上提出了两个推论。可以证明,该方法能够有效地简化逻辑推理。最后,在层次结构模型中分析其推理过程。     

Forecasting of Software Reliability Using Neighborhood Fuzzy Particle Swarm Optimization Based Novel Neural Network

This paper proposes an artificial neural network (ANN) based software reliability model trained by novel particle swarm optimization (PSO) algorithm for enhanced forecasting of the reliability of software. The proposed ANN is developed considering the fault generation phenomenon during software testing with the fault complexity of different levels. We demonstrate the proposed model considering three types of faults residing in the software. We propose a neighborhood based fuzzy PSO algorithm for competent learning of the proposed ANN using software failure data. Fitting and prediction performances of the neighborhood fuzzy PSO based proposed neural network model are compared with the standard PSO based proposed neural network model and existing ANN based software reliability models in the literature through three real software failure data sets. We also compare the performance of the proposed PSO algorithm with the standard PSO algorithm through learning of the proposed ANN. Statistical analysis shows that the neighborhood fuzzy PSO based proposed neural network model has comparatively better fitting and predictive ability than the standard PSO based proposed neural network model and other ANN based software reliability models. Faster release of software is achievable by applying the proposed PSO based neural network model during the testing period.      

基于风险的PKI交叉认证模型研究

探讨了传统的公钥体系结构(PublicKeyInfrastructure,PKI)的缺陷,从信任管理角度,在基于风险的数字证书认证框架基础上,提出了PKI交叉认证的实现模型。模型包括基于风险的信任管理体系结构,终端证书的信任值计算方法及其实现算法,以及证书信任策略。     

PKI多级混合信任模型及其信任路径构建

主要研究了PKI信任模型及其信任路径的构建。对常用的信任模型进行了简要分析,在此基础上提出了一种适合中等规模PKI需要的多级混合模型,引入嵌套证书和信任矩阵的概念,通过预验证的方法,减少用户在验证证书时需要进行的公钥运算的次数,提高了路径寻找和证书验证的效率和速度。     

PKI跨域信任计算方法

针对PKI跨域方案中信任管理偏重身份信任的问题,对PKI下的信任计算进行探讨,为适应域间信任关系动态变化的特点,提出一种基于PKI安全域的跨域信任计算方法,该方法结合PKI的身份信任网络,能够使资源域在设置与外域根CA的信任关系,并监控跨域用户行为后,对外域各信任实体做出合理的信任评价.     

基于主观逻辑的PKI信任评估模型

现有公钥基础设施(PKI)无法实现对信任的细粒度控制。针对该问题,借鉴模块化的信任评估模型,设计一种基于主观逻辑的信任评估模型。利用主观逻辑中的直接信任、推荐信任、合意操作实现信任的建立、传递与评估,通过退化操作实现信任度随时间衰减的拟合,分析非独立的信任混联传递。研究结果表明,该模型能够精确地计算信任度,提高PKI系统的可信性。     

一种求解无约束优化问题的非单调信赖域算法

提出了非单调信赖域算法求解基于锥模型的无约束优化问题,该算法在求解信赖域子问题时充分利用了当前迭代点的一阶梯度信息。提出了一个新的信赖域半径的选取机制,并和经典的信赖域方法作比较分析。设定了一些条件,在这些假设条件下证明了算法是整体收敛的。数值实验结果表明,该算法对基于锥模型的无约束优化问题的求解是行之有效的,拓展了非单调信赖域算法的应用领域。     

PKI信任度模型路径算法研究

分析了分布式环境中信任的特点,总结了目前PKI体制中实体信任的缺陷,介绍了信任度机制以及信任路径中的两种独立路径-不相交路径和连通路径。结合图论中的最可靠路径算法,提出了一种PKI信任度模型中优化的可靠路径算法,提高了信任的准确性。     

基于概率和条件逻辑的PKI信任模型推理

提出一种基于概率和条件谓词逻辑来表示和推导PKI信任模型的方法．该方法用3个二元条件谓词表示不同个体之间的关系,并给出了实体认证规则、信任规则和信任扩展规则，对信任度定义了一个概率模型，该模型能反映约束条件如何影响信任度．概率模型加条件谓词逻辑能够对一个PKI信任模型进行更精确的描述．