资源列表
Graphics
- cette fonction permet de tracer les courbes d un signal
bayes
- 用Matlab语言编写的实现贝叶斯准则，可以很方便的验证贝叶斯准则-Matlab language implementation of Bayesian guidelines, you can easily verify that the Bayesian criteria
fisher
- 用Matlab语言编写的实现fisher准则，可以很方便的验证fisher准则-Fisher guidelines for implementation of the Matlab language, you can easily verify that the fisher criteria
matlab111
- 用来实现模式识别中的贝叶斯准则和fishier分类器，可以进行聚类分析-To pattern recognition, Bayesian criteria and fishier classification, cluster analysis can be carried out
DEmo
- 利用matlab语言实现常微分方程的求解，可以很好的解决常微分方程问题-Matlab language to achieve the solution of ordinary differential equations, can solve the problems of ordinary differential equations
TSP-problem-of-simulated-annealing
- 使用模拟退火方法解决了TSP问题，改进了过程中可能丢失最优解的问题-Optimal solution may be lost in the process of using the simulated annealing method to solve the TSP problem, improved
gfsdgsdfgfdsfg
- matlab 偏微分方程数值计算源代码 偏微分方程数值计算源代码-Matlab Partial Differential Equations Numerical calculation of the source code
cycloid-motion
- 通过matlab绘制一个运动的图，图中为小球摆线运动-Matlab draw a sports figure, the figure for the cycloidal motion of the ball
Wavelet-NN-Id
- 通过小波神经网络实现系统辨识仿真,跟踪效果不错，适合学习小波神经网络的初学者-Wavelet neural network to realize system identification by simulation, the effect is perfect and it is suitable for the beginners
Robot-arm-non-standard-LQR-Control
- 单级机械臂的位置控制，由于需要调整时间和最大输入力矩的要求，程序实现两种非标准的LQR控制-The single-stage manipulator position control, due to the need to adjust the time and the maximum input torque requirements of the program to achieve the two non-standard LQR control
matlab
- 自己2011年12月的神经网络作业，利用神经网络训练： 自组织竞争网络在模式分类中的应用 —患者的某病的发病预测-December 2011, the neural network operation, the use of neural network training: self-organizing competitive network for pattern classification- in patients with the incidence of a disease
jiaoduceliang
- 实现随钻测量中各个角度的校正系数的计算方法，以实现正确角度校正，实现井眼轨迹控制-To achieve with measurement while drilling angle correction factor calculated in order to achieve the correct angle correction, the well trajectory control