基于AD9789的DVB-C调制系统的实现

设计了一个基于AD9789和低功耗FPGA Spartan-6的DVB-C调制系统。介绍了AD9789的基本结构、参数配置以及系统实现方式,给出了系统射频输出信号的实测结果,其性能指标符合国家标准。     

有意义的MD4碰撞攻击(英文)

2005年的欧密会,Wang等提出了一种构造MD4碰撞的有效方法,该方法不仅对寻找随机碰撞有效,还可以用于构造有意义的碰撞。以Wang的技术为基础,进一步分析和探讨了对构造纯文本文件有意义的MD4碰撞,给出了一种构造纯文本文件的有意义MD4碰撞的方法,概率为2-33.77。在1996年的FSE会议上,Dobbertin的"Crypt analysis of MD4"给出了一个有意义的碰撞,而其在开头包含了16个随机字符。这里给出了一个基于Latin-1字符集的有意义的碰撞。     

基于SVM和小波分析的脑电信号分类方法

根据癫痫脑电信号与正常脑电信号波形和能量特征的不同,研究了两种的脑电信号分类方法,一种采用支持向量机SVM(Support Vector Machines)分类器对正常脑电和癫痫脑电进行分类;另一种使用小波分析和支持向量机相结合的方法对脑电进行分类,并比较了这两种方法对正常脑电和癫痫脑电分类的正确率。实验结果表明,小波分析和SVM结合的方法对脑电信号分类可以取得更好的效果,能有效区分癫痫脑电和正常脑电。     

A split least-squares characteristic mixed finite element method for Sobolev equations with convection term

In this paper, a split least-squares characteristic mixed finite element method for a kind of Sobolev equation with convection term is proposed, in which the characteristic method is based on the approximation of the material derivative term, that is, the time derivative term plus the convection term. The resulting least-squares procedure can be split into two independent symmetric positive definite sub-schemes and does not need to solve a coupled system of equations. Theory analysis shows that the method yields the approximate solutions with optimal accuracy in L²(Ω) norm for the primal unknown and in H(div;Ω) norm for the unknown flux, respectively. Numerical examples in one dimension, which are consistent with the theoretical results, are provided to demonstrate the characteristic behavior of this approach.     

Automatic detection of electroencephalographic changes using adaptive neuro-fuzzy inference system employing Lyapunov exponents

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for automatic detection of electroencephalographic changes. Decision making was performed in two stages: feature extraction by computation of Lyapunov exponents and classification by the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Five types of electroencephalogram (EEG) signals were classified by five ANFIS classifiers. To improve diagnostic accuracy, the sixth ANFIS classifier (combining ANFIS) was trained using the outputs of the five ANFIS classifiers as input data. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the saliency of features on classification of the EEG signals were obtained through analysis of the ANFIS. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in classifying the EEG signals.     

基于TMS320F2812的高速数据采集处理系统

介绍一种基于TMS320F2812的多路数据采集系统的设计方案。采用DSP芯片TMS320F2812实现对多路数据的实时采集处理。通过USB2．0将数据传到上位机,由上位机对数据进行具体分析并将结果反馈给DSP进行控制。该系统具有结构简单、可靠性高、使用灵活和性价比高等优点。     

逆P-集合的边界特征与系统状态监测

逆P-集合是具有动态特性的集合模型,逆P-集合的动态特性来自集合内元素(属性)的动态迁移:元素迁入使得集合的边界向外扩展,元素迁出使得集合的边界向内收缩,从而产生扰动的边界和稳定的核。基于上述事实,在逆P-集合的基础上,提出逆P-集合的边界、核的概念和特征,给出逆P-集合与有限普通元素集合之间的关系、边界和核的扰动定理及逆P-集合、边界和核在系统状态监测中的应用。     

Conditions for local almost sure asymptotic stability

In this paper, we investigate local asymptotic stability ensured by the addition of Gaussian white noise into dynamical systems. There are different stability notions for stochastic systems, such as asymptotic stability in probability (ASiP) and uniform almost sure asymptotic stability (UASAS). The local ASiP property is incapable of ensuring that sample paths converge to the origin with probability one, whereas the local UASAS property is capable of it. However, in general, the local UASAS property requires tight conditions. Here, we provide our notion of local almost sure asymptotic stability (local ASAS) to relax the conditions with both almost sure convergence of sample paths to the origin and the existence of bounded (weak) invariant sets. We find that the addition of Gaussian white noise always prevents the origin from being locally UASAS as long as we consider smooth Lyapunov functions; however, it is possible to make the origin locally ASAS. The result is confirmed by a simple example of elimination of unstable equilibria by deliberately adding Gaussian white noise.