Maxiflowminicut

Gibbs sampling算法,生成Ising model的随机样本

H=CIRCLE(CENTER,RADIUS,NOP,STYLE) This routine draws a circle with center defined as a vector CENTER, radius as a scaler RADIS. NOP is the number of points on the circle. As to STYLE, use it the same way as you use the rountine PLOT. Since the handle of the object is returned, you use routine SET to get the best result.

产生L=31的gold序列，又两个移位寄存器输出的模2相加产生。(L = 31 generated sequences of gold, but also two shift registers generate the sum of the output mode 2.)

多目标遗传算法 很好很强大 是一个非常不错的程序(it s good for you)

pid控制模型的matlab源程序，极佳的学习资料，适合学习(the material for the pid control study)

A PIV Post-processing and data analysis toolbox(The PIVMat Toolbox for Matlab contains a set of command-line functions to import, post-process and analyse 2- and 3-components vector fields from PIV (particle image velocimetry), stereo-PIV, DIC (digital image correlation) SS (synthetic schlieren) or BOS (background-oriented schlieren) applications. Main Features: - Import vector fields from PIV (Particle Image Velocimetry) or other related technics, such as DIC (Digital Image Correlation), SS and BOS (Synthetic Schlieren and Background-oriented Schlieren). - Compatibale with files from DaVis (LaVision), DPIVSoft (Meunier & Leweke), VidPIV (Oxford Laser), MatPIV and Optical Flow. - Standard vector field operations: interpolation, filtering (median, Butterworth...), averaging (temporal, spatial, azimuthal...), derivatives computation (vorticity, divergence, strain, Q-factor...) - Fully vectorized: all operations directly apply on arrays of fields (no for loops) - More than 60 functions with full on-line documentation sampl)

按转子磁链定向的矢量控制系统matlab仿真；(Press the rotor flux oriented vector control system matlab simulation )

this go sample code for genetic

knn是一种分类算法，它是基于matlab的一种模式识别的经典算法，一般适用于样本个数较小的样本分类。(KNN, it is classification algorithm based on matlab a pattern recognition of the classic algorithm, generally applied in sample number of smaller sample classification. )

例1 采用动量梯度下降算法训练 BP 网络。 例2 采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。(Example 1 uses the momentum gradient descent algorithm to train the BP network. Example 2 uses the Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, the LM optimization algorithm (trainlm) and the Bayesian regularization algorithm (trainbr), to train the BP network to fit a sine sample with white noise data. )