Chapter-11

说明：  小波分析从基础到高级应用的matlab源码例程~~(Wavelet analysis of matlab source routines ~ ~)

Matlab的模拟退火算法工具箱。并附有sample文件夹，有助于初学者进行学习测试。(The Matlab simulated annealing algorithm toolbox. With the sample folder, will help beginners learn the test.)

poisson问题有限元求解通用程序(线性元). 压缩包内exp.m包含了一个实际问题,matlab下直接运行即可,如效率不高,可适当修改网格参数h.(poisson problem of the finite element procedure for solving general (linear million). exp.m compressed package contains a real problem, matlab can be directly run, such as the efficiency is not high, may be appropriate to amend the grid parameter h.)

数值积分工具箱 这些都是通用集成例程： quadg.m - 高Quad和QUAD8的准确性更换（1-D）quad2dg.m - 集成在一个矩形区域的2-Dquad2dggen.m - 比一般地区一体化的2-D- 超过ND超矩形区域quadndg.m ND集成(Numerical integration toolbox these are universal integrated routines: Quadg.m- Quad and QUAD8(1-D ) quad2dg.m accuracy replacement- integrated in a rectangular area of the2-Dquad2dggen.m than in the general area in the integration of2-D over ND super rectangle quadndg.m ND integration)

LSB implemetation on matlab... with gui... run the .m files

Syplify经典英文教程。内含众多实验例程，Lab 1 Basic Synplify Run；Lab 2 Analyzing Critical Path and Assigning Timing；Lab 3 FSM (Finite State Machine) Compiler Constraints and Attributes(Syplify classic English tutorial. Contains numerous experiments routine, you can help learners to quickly grasp Syplify tips, is a rare foreign experiments tutorial.)

wind power systems with permanent magnet generator in matlab

这是用itpp库编写的卷积码的解码程序。由于用C++库和Intel的MKL库，所以速度飞快。同样的仿真点数， Matlab2012下用了15分半钟，而这个程序仿真只用了半分钟，相当于是matlab速度的30多倍。(This is itpp prepared for the convolutional code decoding process. Because with C++ libraries and Intel' s MKL library, so fast. The same simulation points under Matlab2012 spent 15 and a half minutes, and this program simulation with only half a minute, the equivalent of 30 times the speed of matlab.)

matlab 科学计算 matlab 可视化 微分方程 物理 算法 (matlab matlab visualization in scientific computing algorithms physics equations)

Project Report on State space analysis of Inverted Pendulum,The Rotary Inverted Pendulum is a classic control problem that is explored often as a project in control courses due to its easily developed dynamics combined with its complexity of control design. Although, the problem can be solved using conventional control techniques like PD/PID controllers, we will use some other powerful techniques involving state space analysis. The system is composed of a pendulum attached to the end of a rotary arm controlled by a motor. The control input is in the form of voltage input to the motor. Here our objective is to keep the pendulum in upright position of unstable equilibrium.