kalman

小波变换 采用mallat算法对信号进行四级分解、重构.matlab做的。(wavelet transform algorithm used Mallat four of the signal decomposition and reconstruction. Matlab done.)

3 PRR Parallel Manipulator with GUI Analysis robot to calculate the forward kinematics

single phase active harmonic filter

粒子滤波入门外文经典文献，非常值得一看，有助于理解基本粒子滤波算法。(Particle filter entry of foreign classic literature, well worth a look, help to understand the elementary filtering algorithm.)

利用混合蛙跳算法对未知类别的数据进行分类(Classification of unknown classes by using shuffled frog leaping algorithm)

连续hopfield神经网络的优化思想用于求简单函数极值(the use of hopfield nerural network to achieve the minimum of a function)

Algorithm Given are P training pairs {X1,d1,X2,d2....Xp,dp}, where Xi is (n*1) di is (n*1) No of Categories=R. i=1,2,...P Yi= Augmented input pattern( obtained by appending 1 to the input vector) i=1,2,…P In the following, k denotes the training step and p denotes the step counter within the training cycle Step 1: c>0 , Emin is chosen, Step 2: Weights are initialized at w at small values, w is (n+1)*1. Counters and error are initialized. k=1,p=1,E=0 Step 3: The training cycle begins here. Input is presented and output computed: Y=Yp, d=dp Oi=f(wtY) for i=1,2,….R Step 4: Weights are updated: wi=wi+1/2c(di-oi)Y for i=1,2,…..R. Step 5: Cycle error is computed: E=1/2(di-oi)2+E for i=1,2,…..R. Step 6: If p<P then p=p+1,k=k+1, and go to Step 3: Otherwise go to Step 7. Step 7: The training cycle is completed. For E=0,terminate the training session. Outputs weights and k. If E>0,then E=0 ,p=1, and enter the new training cycle by going to step 3.

曲线拟合功能 实现曲线不同方式的拟合，为初学matlab做曲线拟合(Curve fitting function curve of different fitting )

用遗传算法优化参数的递归T-S模糊神经网络学习算法，值得一看。(Parameter optimization using genetic algorithm recursive TS fuzzy neural network learning algorithm, worth a visit.)

it s knn simulation by matlab toolbox