基于MATLAB的AVI视频影像分解与压缩

为了实现对AVI(Audio Video Interleaved)文件中视频影像的分析和处理,提出了一种根据AVI文件的存储结构、利用Matlab中的音视频处理函数aviread等编程的方法,将AVI文件中的视频数据流读出并存储为一系列BMP文件,再进行小波变换压缩后写入AVI文件.利用该方法,实现了AVI视频影像的分解、合成及压缩,编程简单、数据处理可靠、程序运行高效.     

Stability and control of nonlinear systems described by retarded functional equations: a review of recent results

This paper reports on recent results in a series of the work of the authors on the stability and nonlinear control for general dynamical systems described by retarded functional differential and difference equations. Both internal and external stability properties are studied. The corresponding Lyapunov and Razuminkhin characterizations for input-to-state and input-to-output stabilities are proposed. Necessary and sufficient Lyapunov-like conditions are derived for robust nonlinear stabilization. In particular, an explicit controller design procedure is developed for a new class of nonlinear time-delay systems. Lastly, sufficient assumptions, including a small-gain condition, are presented for guaranteeing the input-to-output stability of coupled systems comprised of retarded functional differential and difference equations.     

Accurate evaluation of Green’s functions in a layered medium by SDP-FLAM

Based on local Taylor expansions on the complex plane, a method for fast locating all modes (FLAM) of spectral-domain Green’s Functions in a planar layered medium is developed in this paper. SDP-FLAM, a combination of FLAM with the steepest descent path algorithm (SDP), is employed to accurately evaluate the spatial-domain Green’s functions in a layered medium. According to the theory of complex analysis, the relationship among the poles, branch points and Riemann sheets is also analyzed rigorously. To inverse the Green’s functions from spectral to spatial domain, SDP-FLAM method and discrete complex image method (DCIM) are applied to the non-near field region and the near filed region, respectively. The significant advantage of SDP-FLAM lies in its capability of calculating Green’s functions in a layered medium of moderate thickness with loss or without loss. Some numerical examples are presented to validate SDP-FLAM method. Supported by the National Natural Science Foundation of China (Grant No. 60621002), and the State Key Development Program for Basic Research of China (Grant No. 2009CB320200)     

Cryptanalysis of RSA for a special case with d > e

In this paper, we study the RSA public key cryptosystem in a special case with the private exponent d larger than the public exponent e. When N ^0.258 ⩽ e ⩽ N ^0.854, d > e and satisfies the given conditions, we can perform cryptanalytic attacks based on the LLL lattice basis reduction algorithm. The idea is an extension of Boneh and Durfee’s researches on low private key RSA, and provides a new solution to finding weak keys in RSA cryptosystems. Supported partially by the National Basic Research Program of China (Grant No. 2003CB314805), the National Natural Science Foundation of China (Grant Nos. 90304014 and 60873249), and the Project funded by Basic Research Foundation of School of Information Science and Technology of Tsinghua     

Statistical learning makes the hybridization of particle swarm and differential evolution more efficient—A novel hybrid optimizer

This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics—differential evolution (DE) and particle swarm optimization (PSO). In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality. Supported by the National Natural Science Foundation of China (Grant No. 60374069), and the Foundation of the Key Laboratory of Complex Systems and Intelligent Science, Institute of Automation, Chinese Academy of Sciences (Grant No. 20060104)     

单片机中基于查表法的多变量函数求解方法设计

针对多变量非线性复杂函数关系式在单片机中难以实现的问题,提出了一种快速有效的查表求解算法。首先建立顺序存储数据块,接下来查找输入变量在已存变量存储块中的自然序号,最后利用查得的变量自然数序号及事先确定的算法查找这些变量所对应的函数值的存储地址,进而得到计算结果。实现了非线性复杂关系式的快速精确求解,可推广于各种运算能力有限的单片机,提高了单片机的整体使用效率。     

基于快速回归算法的RBF神经网络及其应用

针对径向基神经网络(RBFNN)中存在的径向基函数中心的数F1及其位置难以确定的问题,提出了一种新型的基于快速回归算法(FRA)的RBFNN.采用快速回归算法,不但能够确定RBF的中心和中心个数,而且能够求出隐含层到输出层的权重.通过一元函数拟合和Mackey-Glass混沌时间序列预测的仿真,验证了该网络的有效性与实用性.     

RBF神经网络在红外CO_2传感器压力补偿中的应用研究

在红外CO2传感器的测量过程中,环境总压是一个重要的影响因素。在环境总压变化的情况下做好压力补偿得出正确的CO2气体分压值,对提高传感器的测量精度有重要意义。提出一种基于聚类和梯度法的径向基函数(RBF)神经网络方法,利用它的局部逼近特性,建立起其在红外CO2传感器的非线性压力补偿中的网络模型。实验结果表明:该应用收到了良好的效果。     

一类切换模糊时滞系统的状态反馈控制

针对切换模糊时滞系统,根据平行分布补偿算法,设计了模糊状态反馈控制器.使用切换技术及单Lyapunov函数和多Lyapunov函数方法,给出了这一类切换模糊时滞系统渐近稳定的充分条件及切换律.仿真结果表明了方法的有效性.