Degreeedrz

对车载倒立摆的伺服系统进行设计，实现对其的控制作用(Inverted pendulum on-board servo system design, implementation, control of their role in)

说明：  模糊聚类和模式识别的具体应用算法，详细的计算说明(Fuzzy clustering and pattern recognition algorithm for specific applications, detailed calculations show)

levelset的matlab工具箱。内涵说明文档，有实例程序(levelset the Matlab toolbox. Connotations of documentation, sample program)

关于维特比的一些仿真程序什么的，希望对你有用(About the Viterbi what some simulation program, and I hope useful to you)

利用matlab软件获得彩色图像的特征值以及生成72维一维向量(Matlab software using color images, as well as the characteristic values to generate one-dimensional 72-dimensional vector)

this function plots a cube

本文基于毕肖普法和蒙特卡洛法,利用MATLAB编程软件计算了边坡结构的失效概率Pf和对应可靠指标β.在计算上述Pf和对应β时,考虑了土体三个主要基本参数(重度γ、内摩擦角(Ψ)、粘聚力c)的随机特性.利用MATLAB程序的计算结果表明,随机变量对边坡可靠度的影响与基本随机参数对抗滑反力的贡献大小有关,即,贡献大的基本随机参数,它的随机波动对结构失效概率Pf的影响也较大,反之亦然.另外,基于MATLAB的算例计算结果还表明:边坡结构失效概率Pf对内摩擦角(Ψ)较敏感,而对重度y和粘聚力c次之.其次,当同时考虑三个随机变量的联合波动对Pf的影响时发现,当它们在小范围内随机波动时,其联合特性对Pf的影响较敏感,但当它们在大范围内随机波动时,Pf主要受敏感随机变量的影响,而三个随机变量联合作用对Pf的影响和敏感随机变量(Ψ)单独作用时相差不大.由此可见,在实际边坡工程可靠性分析中,土体内摩擦角起主要作用,不容忽视.(Based Bishop method and Monte Carlo method, using MATLAB programming software to calculate the failure probability Pf and the corresponding slope reliability index β structure in the calculation of the above Pf and the corresponding β, consider the three main basic soil parameters (severe γ internal friction angle (Ψ), cohesion c) of the random nature of calculation results using MATLAB program shows that the influence of random variables on the reliability of the basic random slope parameters against anti- slip contribution to the size of the force , that is , the contribution the basic parameters of large random , random fluctuations which affect the probability of structural failure Pf is also larger , and vice versa addition, the calculation based on MATLAB numerical results also show that : the structure of slope failure probability Pf internal friction angle (Ψ) more sensitive , while severe and cohesion c y followed . Secondly, when taking into account the impact of the joint fl)

it is for macrowawe and antenna that is very good

用最大似然估计训练分类器，用Train.txt里的数据进行训练，用Test.txt的数据进行性能检测(Use the maximum likelihood estimation training classifier, use the data in Train.txt to train the classifier and use the data in Test.txt to test the performance of the classifier)

单纯形法的灵敏度分析 有需要的人可以看看 (matlab )