FIR

DateConvert：简单而快速的日期转换 DateConvert转换DATESTR（0）格式的日期向量或序列号和日期向后。 Matlab的DATENUM，DATEVEC和DATESTR接受各种不同意见，但结果他们是缓慢的。如果输入格式正是众所周知，转换可以更快： DATENUM（ 17 - 10 - 2009 11时08分23秒 ）：2.97秒 DateConvert（ 17 - 10 - 2009 11时08分23秒 ， 号码 ）：0.039秒 =>“1.3％（1000环，1.5GHz的奔腾- M的，利用Matlab 7.7） DateConvert不*不*验证作为Matlab的日期函数输入日期： DATEVEC（ 32 - 2 - 2008 25:62:63 ）的答复[2008 3 4 2 2 7] DateConvert（ 32 - 2 - 2008 25:61:67 ， 载体 ）的答复[2008 2 32 25 61 67]！ 因此DateConvert几乎微不足道，但对速度进行了优化。我需要时间排序200 000邮票，并从217个减少到11秒的时间。 请运行单元测试TestDateVec检查的有效性和速度。 测试：利用Matlab 6.5，7.7，7.8，winxp的，32位。 纯Matlab代码，所以兼容性的MacOS，Linux操作系统，64位预期。 英语月份名称是必要的。(DateConvert: Simple but fast date conversion DateConvert converts the DATESTR(0) format to a date vector or serial date number and backwards. Matlab s DATENUM, DATEVEC and DATESTR accept a variety of inputs, but in consequence they are slow. If the input format is exactly known, the conversion can be much faster: DATENUM( 17-Oct-2009 11:08:23 ): 2.97 sec DateConvert( 17-Oct-2009 11:08:23 , number ): 0.039 sec => 1.3 (1000 loops, 1.5GHz Pentium-M, Matlab 7.7) DateConvert does*not* validate the input date as Matlab s date functions: DATEVEC( 32-Feb-2008 25:62:63 ) replies [2008 3 4 2 2 7], DateConvert( 32-Feb-2008 25:61:67 , vector ) replies [2008 2 32 25 61 67] ! So DateConvert is nearly trivial, but optimized for speed. I needed it for sorting 200 000 time stamps and reduced the time from 217 to 11 sec. Please run the unit-test TestDateVec to check validity and speed. Tested: Matlab 6.5, 7.7, 7.8, WinXP, 32bit. Pure Matlab code, so compat)

有关matalab方面的仿真文献，希望大家有好的东西都能够共享！(Matalab aspects related to the simulation literature, I hope everyone has good things to share!)

说明：  Iris数据集的分类程序，包括线性分类器实验，BP网络分类器实验，以及异或数据的BP网络分类实验，外带试验报告(Iris data set of classification procedures, including linear classification experiment, BP network classifier experiments, and different BP networks or data classification experiment, take-test report)

基于matalb/simulink的模糊PID控制仿真。波形良好。 包括常规PID控制与模糊PID的对比仿真，以及加入延时的系统仿真和加入干扰后的系统仿真，均已经过调试，波形结果很好。 大家可直接用于借鉴学习。(Fuzzy PID control simulation based on matalb/simulink. Good waveform. Including the conventional PID control and fuzzy PID contrast simulation, and adding delay system simulation and adding interference after the system simulation, have been debugging, waveform results are very good. We can learn from them directly.)

GuassSeidel迭代法,得到完整的迭代数据和最中运算结果，可以自行控制误差以及迭代次数(GuassSeidelMethodForLinearEquations)

MPI Config message, structures, and Pages.

Nonlinear Finite Elements for Continua and Structures英文原版第二版和代码，介绍非线性有限元的基本方法，以及非线性有限元的前沿研究(Nonlinear Finite Elements for Continua and Structures original English version and the second code, the basic nonlinear finite element method described, as well as cutting-edge research in nonlinear finite element)

给出了机械手的数学建模，实现rbf自适应控制建模和控制器，最后通过matlab程序仿真实现。(The mathematical modeling of robot to achieve the rbf adaptive control modeling and controller, and finally through simulation matlab program to achieve.)

说明：  四旋翼无人机是一种可以被遥控也可以在无人为控制的状态下执行预定任务的飞行器，与传统直升机相比四旋翼飞行器的机械结构简单，且具有高精度，灵活精度以及较低成本的特点，被广泛用于军事侦察，农艺播撒、快递派送、摄影工作等领域。四旋翼飞行器自身具有欠驱动、多变量、非线性等特性，在外界的噪声干扰情况下，增加了四旋翼无人机的不稳定以及控制系统的设计难度。所以对四旋翼飞行器的位姿控制的研究，可以开拓科研人员对控制算法以及滤波算法的认知，具有重要的研究意义。(Four-rotor UAV is a kind of aircraft that can be controlled remotely or perform scheduled tasks without human control. Compared with traditional helicopters, the Four-rotor UAV has simple mechanical structure, high precision, flexible precision and low cost. It is widely used in military reconnaissance, agricultural broadcast, express delivery, photography and other fields. Four-rotor UAV has the characteristics of under-actuation, multi-variable and non-linearity. Under the circumstance of external noise, the instability of Four-rotor UAV and the difficulty of control system design are increased. Therefore, the research on attitude control of Four-rotor aircraft can broaden the knowledge of control algorithm and filtering algorithm for researchers, and has important research significance.)

sobel edge detector matlab code with comments