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matlab教程，内容为ppt格式的，对于matlab入门有详细的介绍(matlab tutorial ppt format content, for a detailed description entry matlab)

MARKOv的应用 Step 1，求出各食品数据的增长率； Step 2，编程，使快速上升（>=0.03） ，在程序中用“2”表示；缓慢上升 (0,0.03)，在程序中用“1”表示；相对不变 0，在程序中用“0”表示；缓慢下降(-0.03,0) ，在程序中用“-1”表示；快速下降 (<=-0.03)，在程序中用“-2”表示；得到各类食品在不同时期的 ； Step 3，统计相邻增长率变化的一致的次数 ，就菜籽油而言，在2010-3-5到2011-3-15，其增长率为先快速增长后相对不变出现的次数为‘20’=1；具体42中食品的输出情况见附录； Step 4，对每一种食品，分五类进行叠加求和，分别为“先快速增长”、“先缓慢增长”、“先相对不变”、“先缓慢下降”、“先快速下降”；得到 ； Step 5，求出一步转移概率矩阵E ；即 每行的每五个数据依次与对应的 相除，得到概率矩阵E 的一行； Step 6，使用求出的一步转移概率矩阵E ，并求出不同时期的状态概率(MARKOv application Step 1, to obtain the growth rate of each food data Step 2, the programming, so fast rise (> = 0.03), in the program with " 2" slowly rising (0,0.03), used in the program " 1" indicates relatively constant 0, by the program " 0" indicates slow decline (-0.03,0), in the program by " -1" rapid decline (< =- 0.03), in the program with " -2" means get all kinds of food at different times Step 3, the same number of adjacent growth statistics change on rapeseed oil, in 2010-3-5 to 2011-3-15, Its growth rate is relatively rapid growth of the number of times after the first change occurs is ' 20' = 1 42 Output of specific food in Appendix Step 4, for each kind of food, five points are superimposed sum, respectively, " First of rapid growth," " first slow growth" , " first relatively unchanged" , " first slow down" , " first rapid decline" get Step 5, to obtain a step)

about maximum peak power tracking

卡尔曼滤波程序，都是基础的，可以直接套用的，比较方便(Kalman filtering process, are based, can be directly applied, more convenient)

NonBinary EXIT chart design

说明：  实现组合导航仿真，扩展卡尔曼滤波算法，比较简洁(Realization of Integrated Navigation Simulation)

件里包含了跳频信号的产生的程序。调跳信号的产生及应用(Cases where the signal contains a frequency-hopping generation process. Tone signal generation and application of jump)

语音识别系统，在静音环境比较准确，但是假若有噪音或者其他情况会有问题，附预处理部分(Speech recognition system, in the quiet environment is accurate, but if there are noise problems or other conditions will be attached to some pretreatment)

GloptiPoly 3: moments, optimization and semidefinite programming. Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem of Moments (GPM), an infinite-dimensional optimization problem which can be viewed as an extension of the classical problem of moments [8]. From a theoretical viewpoint, the GPM has developments and impact in various areas of mathematics such as algebra, Fourier analysis, functional analysis, operator theory, probability and statistics, to cite a few. In addition, and despite a rather simple and short formulation, the GPM has a large number of important applications in various fields such as optimization, probability, finance, control, signal processing, chemistry, cristallography, tomography, etc. For an account of various methodologies as well as some of potential applications, the interested reader is referred to [1, 2] and the nice collection of papers [5].(GloptiPoly 3: moments, optimization andsemidefinite programming.Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem ofMoments (GPM), an infinite-dimensional optimization problem which can be viewed asan extension of the classical problem of moments [8] . From a theoretical viewpoint, theGPM has developments and impact in various areas of mathematics such as algebra, Fourier analysis, functional analysis, operator theory, probability and statistics, to citea few. In addition, and despite a rather simple and short formulation, the GPM has alarge number of important applications in various fields such as optimization, probability, finance, control, signal processing, chemistry, cristallography, tomography, etc. For anaccount of various methodologies as well as some of potential applications, the interestedreader is referred to [ 1, 2] and the nice collection of papers [5].)

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