UndoRedo

使用块匹配法的三步搜索对视频中的两帧图象进行预测编码(Use block matching method for video of the three-step searching two frames image forecast coding)

MATLAB 阻抗计算例子1，很有参考价值。。(MATLAB impedance calculation example 1, a good reference. .)

说明：  w-w1各教徒和w1个非教徒在海上遇险，必须将一半的人投到海中，其余的人才能幸免，于是想了个办法w人围成一圈从第一人开始报数，数到第w2个就将其人丢入海中，又从下个人数，数到第w2个人又丢入海中，依次循环，怎样排才使投入大海的都是非教徒(w-w1 and w1 of all non-believers believers in distress at sea, half of them must be invested in the sea, the others can be spared, so think of one way to w people form a circle from the first people began to count off a few to the first w2 one would be thrown into the sea of its people, and from under the personal number, the number of individuals to the first w2 then thrown into the sea, followed by recycling, how to make it into the sea row are non-believers)

export iges from matlab to autocad

基于蒙特卡罗方法的试卷难度分布研究,Monte Carlo method based on the difficulty of distribution of papers(Monte Carlo method based on the difficulty of distribution of papers)

船舶运动及控制建模，基本上各个程序都有，方便实用。(Ship motion and control model, various programs have substantially, convenient and practical.)

EMD的Toolbox及使用方法 经验模态分解（Empirical Mode Decomposition, 简称EMD）是由美国NASA的黄锷博士提出的一种信号分析方法.它依据数据自身的时间尺度特征来进行信号分解, 无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。正是由于这样的特点, EMD 方法在理论上可以应用于任何类型的信号的分解, 因而在处理非平稳及非线性数据上, 具有非常明显的优势。所以, EMD方法一经提出就在不同的工程领域得到了迅速有效的应用, 例如用在海洋、大气、天体观测资料与地震记录分析、机械故障诊断、密频动力系统的阻尼识别以及大型土木工程结构的模态参数识别方面。本工具书主要分以下几个部分：导论、非稳态信号介绍、一维时频信号分解、二维时频信号分解、时频影像信息提取等。 (Time frequency toolbox for use with MATLAB The Time-Frequency Toolbox has been mainly developed under the auspices of the French CNRS (Centre National de la Recherche Scientifique). It results from a research effort conducted within its Groupements de Recherche ”Traitement du Signal et Images” (O. Macchi) and ”Information, Signal et Images” (J.-M. Chassery). Parts of the Toolbox have also been developed at Rice University, when one of the authors (PG) was visiting the Department of Electrical and Computer Engineering, supported by NSF. Supporting institutions are gratefully acknowledged, as well as M. Guglielmi, M. Najim, R. Settineri, R.G. Baraniuk, M. Chausse, D. Roche, E. Chassande-Mottin, O. Michel and P. Abry for their help at different phases of the development.)

使用matlab做的离散时间单位冲激响应(Discrete-time unit impulse response)

matlab版本PQ分解法的潮流计算程序 (PQ decomposition matlab version of the trend calculation program)

Motion tracker project on matlab