MergingSnakes

matlab code about kalman filter

基于自适应的遗传算法求解，比标准遗传算法具有更加良好的解集，收敛性能更好(The solution based on adaptive genetic algorithm has better solution set and better convergence than standard genetic algorithm.)

矩形谐振腔中TEmnp模的场分布，matlab程序，改变程序中mnp可得到不同模式的场分布，结果正确(Matlab program of the field distribution of TEmnp in the rectangular resonant cavity, change the MNP value in the program can get the result of different mode field distribution, and the result is correctthe field distribution of TEmnp in the rectangular resonant cavity, the MNP value in the program can get the correct result of different mode field distribution)

双光纤耦合器的建模仿真，对耦合器的透过率参数分析研究(Dual optical fiber coupler of modeling and simulation of coupler transmittance analysis of parameters)

基于二次型性能指标学习算法的单神经元自适应PID控制，采用二次型性能指标来计算控制律可以得到所期望的优化效果。(Quadratic performance index based on the learning algorithm of single neuron adaptive PID control, quadratic performance index used to calculate the control law can be expected to optimize the effect.)

Short code to create shading around a mean. Input is a matrix with rows of observations

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models.

ofdm系统的基本系统图仿真，包括调制，IFFT，解调，FFT等(The basic system diagram ofdm system simulation, including the modulation, IFFT, demodulation, FFT, etc.)

采用Matlab工具箱函数建立神经网络，对一些基本的神经网络参数进行了说明，深入了解参考Matlab帮助文档。 (Using Matlab toolbox functions to establish neural networks, some of the basic neural network parameters are described to understand the reference to Matlab help documentation.)

这是我在通信原理课程设计中自己做的程序，是关于数字调制中几个方法的画图与各自的误码率分析(包括画图），供大家参考(This is my design in the communication theory course do their own procedures, several methods of digital modulation in the drawing and their error rate analysis (including drawing), for your reference)