moesp

matlab语言编写的常见图像处理程序，包括高斯滤波、维纳滤波等程序(matlab language of the commonly used image processing procedures, including the Gaussian filtering, Wiener filtering,)

用于激光谐振腔的计算，采用早期的foxli算法。

一个MATLAB工具箱，可以进行快速而可靠的听觉阈值的计算！目前很少有类似的方法。(A MATLAB toolbox for rapid and reliable auditory threshold estimation)

Finite element code for solving eigen value problem.

汽轮机转子系统前三阶临界转速的传递矩阵法(Turbine rotor system critical speed before the third-order transfer matrix method)

Sullivan关于FTDT经典文章的MATLAB翻译，第三章第二个例子的源程序。(Sullivan article on FTDT classic MATLAB translation of Chapter III of the second example of the source.)

= lorentzfit （× ） lorentzfit 符合输入（× ）与罗伦兹功能的形式 “ （× ）= 1 / （（- 2）^ 2 + 3号） 输入 ：因变量值[ 是] （× ） × ：独立变量的值 输出功率 一：名单[ 1 2 3 ] 罗伦兹参数 示例 × = - 16:0.1:35 = 19.4 / （（- 7）^ 2 + 15.8）+ randn （大小（× ）/ 10 ） = lorentzfit （× ） 杰瑞德·威尔斯 11 / 15 / 11 杰瑞德威尔斯[ 点] [在] [ 点] 教育公爵(a = lorentzfit(y,x) LORENTZFIT fits the input Y(X) with a Lorentzian function of the form Y (X) = A1./((X- A2).^2+ A3) INPUTS Y : Dependent variable values [Y(X)] X : Independent variable values OUTPUT A : List of Lorentzian parameters [A1 A2 A3] EXAMPLE x =-16:0.1:35 y = 19.4./((x- 7).^2+ 15.8)+ randn(size(x))./10 a = lorentzfit(y,x) Jered R Wells 11/15/11 jered [dot] wells [at] duke [dot] edu)

RS码编码的源代码，直接复制出来粘贴在新建工程即可用(RS coding source code, paste copied directly out ready for use in new construction)

用matlab来做随机模糊模拟的计算，清华刘宝锭《不确定理论》中的算例(Calculated using matlab to do a random fuzzy simulation, Qinghua Liu ingot "Uncertainty Theory" in the numerical example)

书名：现代控制引论教程 Matlab辅助实验 本教材共9章。第1章介绍了经典控制论的主要内容，这是研究控制论问题时最初引入的理论和方法；第2章是现代控制论采用的状态空间描述，包括连续时间和离散时间空间模型；第3章是系统状态分析；第4章介绍了现代控制论的两个标志性的内容．即系统状态的能控性和能观性，以及能控性和能观性的判定等内容；第5章介绍了系统各种稳定性的概念和判别方法；第6章是在前5章分析的基础上，讨论了系统综合问题，如极点配置、镇定等；第7章介绍了最优控制的基本方法——极小值原理和动态规划法；第8章和第9章分别对控制论的两个分支：随机系统的状态滤波与控制和自适应控制方面等内容作了基本介绍。 (Title: Introduction to modern control experiment textbook tutorial of Matlab including 9 Chapters: Chp1 introduces the main content of classical control theory, cybernetics is the study of this problem first introduced the theory and methods in Chp2 of the modern control theory using state-space description, including the continuous time and discrete time space model Chp3 is the system state analysis Chp4 describes the modern control theory, the two iconic content. The state of the system controllability and observability and controllability and observability of the decision, etc. Chp5 introduces the concept of system stability and discrimination of various methods Chp6 is based on the former 5 chapters and discusses the systems integration issues, such as pole placement, stabilization, etc. Chp7 describes the basic method of optimal control- minimum principle and dynamic programming Chp8 and 9, respectively, on control theory The two branches: the state of stochastic)