安全协议认证的形式化方法研究

安全协议认证是网络安全领域中重大课题之一。形式化方法多种多样。该文首先论述了模型检测技术及其在安全协议验证中的应用,然后介绍了各种定理证明方法和定理证明工具,接着讨论其它形式化验证方法,最后论述形式化方法的一些研究方向。     

Optimal classification methods for mapping agricultural tillage practices

The classification of agricultural tillage systems has proven challenging in the past using traditional classification methods due to the similarity of spectral reflectance signatures of soils and senescent crop residues. In this study, five classification methods were examined to determine the most suitable classification algorithm for the identification of no-till (NT) and traditional tillage (TT) cropping methods: minimum distance (MD), Mahalanobis distance, Maximum Likelihood (ML), spectral angle mapping (SAM), and the cosine of the angle concept (CAC). A Landsat ETM+ image acquired over southern Michigan and northern Indiana was used to test these classification methods. Each classification method was validated with 293 ground truth sampling locations collected commensurate with the satellite overpass. Classification accuracy was then assessed using error matrix analysis, Kappa statistics, and tests for statistical significance. The results indicate that of the classification routines examined, the two spectral angle methods were superior to the others. The cosine of the angle concept algorithm outperformed all the other classification routines for tillage practice identification and mapping, yielding an overall accuracy of 97.2% (Kappa=0.959).     

Application of Kernel-Based Feature Space Transformations and Learning Methods to Phoneme Classification

This paper examines the applicability of some learning techniques to the classification of phonemes. The methods tested were artificial neural nets (ANN), support vector machines (SVM) and Gaussian mixture modeling (GMM). We compare these methods with a traditional hidden Markov phoneme model (HMM), working with the linear prediction-based cepstral coefficient features (LPCC). We also tried to combine the learners with linear/nonlinear and unsupervised/supervised feature space transformation methods such as principal component analysis (PCA), independent component analysis (ICA), linear discriminant analysis (LDA), springy discriminant analysis (SDA) and their nonlinear kernel-based counterparts. We found that the discriminative learners can attain the efficiency of HMM, and that after the transformations they can retain the same performance in spite of the severe dimension reduction. The kernel-based transformations brought only marginal improvements compared to their linear counterparts.     

Parallel and Systolic Solution of Normalized Explicit Approximate Inverse Preconditioning

A new class of normalized approximate inverse matrix techniques, based on the concept of sparse normalized approximate factorization procedures are introduced for solving sparse linear systems derived from the finite difference discretization of partial differential equations. Normalized explicit preconditioned conjugate gradient type methods in conjunction with normalized approximate inverse matrix techniques are presented for the efficient solution of sparse linear systems. Theoretical results on the rate of convergence of the normalized explicit preconditioned conjugate gradient scheme and estimates of the required computational work are presented. Application of the new proposed methods on two dimensional initial/boundary value problems is discussed and numerical results are given. The parallel and systolic implementation of the dominant computational part is also investigated.     

New Bounds for Timed Event Graphs Inspired by Stochastic Majorization Results

In this paper, we develop new bounding methodologies of max-plus linear systems inspired by results dealing with comparison of stochastic processes. The methods developed in this paper are based on preorder and monotonicity. These methods allow us to obtain comparisons of timed event graphs (TEGs) by comparing their dater dynamical equations. We illustrate with a simple example of Baccelli and Hong (2000) that part of the results provides new approach for computing lower and upper bounds of the Lyapunov exponent of discrete event systems (DES). However the problem of the computation of bounds on Lyapunov exponent requires thorough investigations which are beyond the scope of this work.     

Optimal evaluation of generalized Euler angles with applications to control

Given two linearly independent matrices in so(3), Z₁ and Z₂, every rotation matrix, X_f∈SO(3), can be written as the product of alternate elements from the one-dimensional subgroups corresponding to Z₁ and Z₂, namely X_f=e^Z₁t₁e^Z₂t₂e^Z₁t₃?e^Z₁t_s. The parameters t_i, i=1,…,s are called Generalized Euler Angles. In this paper, the minimum number of factors required for the factorization of X_f∈SO(3), as a function of X_f, is evaluated. An algorithm is given to determine the generalized Euler angles, in the optimal factorization. The results can be applied to the bang-bang control, with minimum number of switches, of some classical and quantum systems.     

Modelling and verification of delay-insensitive circuits using CCS and the Concurrency Workbench

The modelling of delay-insensitive asynchronous circuits in the process calculus CCS is addressed. MUST-testing (rather than bisimulation) is found to support verification both of the property of delay-insensitivity and of design by stepwise refinement. Automated verification is possible with a well-known tool, the Edinburgh Concurrency Workbench.     

A probabilistic spectral framework for grouping and segmentation

This paper presents an iterative spectral framework for pairwise clustering and perceptual grouping. Our model is expressed in terms of two sets of parameters. Firstly, there are cluster memberships which represent the affinity of objects to clusters. Secondly, there is a matrix of link weights for pairs of tokens. We adopt a model in which these two sets of variables are governed by a Bernoulli model. We show how the likelihood function resulting from this model may be maximised with respect to both the elements of link-weight matrix and the cluster membership variables. We establish the link between the maximisation of the log-likelihood function and the eigenvectors of the link-weight matrix. This leads us to an algorithm in which we iteratively update the link-weight matrix by repeatedly refining its modal structure. Each iteration of the algorithm is a three-step process. First, we compute a link-weight matrix for each cluster by taking the outer-product of the vectors of current cluster-membership indicators for that cluster. Second, we extract the leading eigenvector from each modal link-weight matrix. Third, we compute a revised link weight matrix by taking the sum of the outer products of the leading eigenvectors of the modal link-weight matrices.     

Blind colour separation of H&E stained histological images by linearly transforming the colour space

Blind source separation methods aim to split information into the original sources. In histology, each dye component attempts to specifically characterize different microscopic structures. In the case of the hematoxylin–eosin stain, universally used for routine examination, quantitative analysis may often require the inspection of different morphological signatures related mainly to nuclei patterns, but also to stroma distribution. Stain separation is usually a preprocessing operation that is transversal to different applications. This paper presents a novel colour separation method that finds the hematoxylin and eosin clusters by projecting the whole space to a folded surface connecting the distributions of a series of planes that divide the cloud of H&E tones. The proposed method produces density maps closer to those obtained with the colour mixing matrices set by an expert, when comparing with the density maps obtained using nonnegative matrix factorization (NMF), independent component analysis (ICA) and a state‐of‐the‐art method. The method has outperformed three baseline methods, NMF, Macenko and ICA, in about 8%, 12% and 52% for the eosin component, whereas this was about 4%, 8% and 26% for the hematoxylin component.     

基于8PSK 和16PSK 调制的全双工RoF 系统研究

误码率(bit error rate, BER)是信号传输质量的重要衡量指标,为了对比分析8进制相移键控(eight hexadecimal phase shift keying, 8PSK)与16进制相移键控(sixteen hexadecimal phase shift keying, 16PSK)信号的传输性能,建立了一个全双工光载无线通信(radio over fiber, RoF)链路模型。系统的下行链路是对基于马赫增德尔调制器(Maher-Zehnder modulator, MZM)的抑制奇次边带两路信号,分别进行8PSK和16PSK调制。上行链路是取下行链路中一路未被调制的抑制奇次边带信号,作为上行基带信号的载波信号,节约系统的成本。该系统分别在不同的光信噪比(optical signal to noise ratio, OSNR)和不同传输距离条件下,仿真分析了下行链路两种调制信号的光谱图及误码率曲线,通过分析接收信号的星座图和误码特性证明:与16PSK信号相比,当OSNR 25时, 8PSK信号误码率量级可以达到10-4(lg BER-3),当传输距离为40 km时, 8PSK的误码率为4.8×10-3(lg BER=-2.32),仍然可以有效传输数据信息。且在不同OSNR和不同传输距离条件下, 8PSK的误码率均低于16PSK,因此8PSK具有更可靠的传输性能,且更适用于远距离传输。