suijijianzhen

说明：  由matlab开发的hybrid系统的描述语言，用于系统的建模、仿真、最优控制等。(from Matlab development of the hybrid system description language for the modeling, simulation, Optimal control.)

The codes included here require Matlab platform 7.0.0 or higher. The source codes have been written by the students who have undergone this subject. The codes are problem specific and not general. The principle aim was to develop softwares for illustration of computational methods and are generally far from optimal. Knowledge of any computer language is sufficient to change the parameters in the codes. A person well versed in Matlab should be able to modify these codes or write their own. It is a common knowledge that understanding the codes written by others is not a pleasant experience. Therefore, useful comments have been added in the codes to help users.(The codes included here require Matlab platform 7.0.0 or higher. The source codes have been written by the students who have undergone this subject. The codes are problem specific and not general. The principle aim was to develop softwares for illustration of computational methods and are generally far from optimal. Knowledge of any computer language is sufficient to change the parameters in the codes. A person well versed in Matlab should be able to modify these codes or write their own. It is a common knowledge that understanding the codes written by others is not a pleasant experience. Therefore, useful comments have been added in the codes to help users.)

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.

mpeg1视频中的I帧以及P帧编码算法在matlab中的模拟(mpeg1 video of I frames, as well as P-frame coding algorithm of the simulation in matlab)

用matlab实现KNN算法 用matlab实现KNN算法 用matlab实现KNN算法 (using matlab to implement K-Nearest Neighbour classification.)

说明：  9节点PQ算法9节点PQ算法9节点PQ算法9节点PQ算法(nine bus)

machine learning 方面有关于Classification fundamentals的资料，语言是python(Classification fundamentals aspects of machine learning have information about language is python)

用有效折射率法计算长周期光纤光栅的透射光谱情况，即是通过有效折射率算法，找出损耗峰（共振峰）。(Simulate transmission spectrum of LPFG via using effect refractive index algorithm. )

用于计算庞加莱截面的MATLAB的源程序(MATLAB Program for Making Poincare Section)

用matlab开发语言实现的遗传算法例程，实现tsp问题的解答(Using matlab programming language implementation of genetic algorithm routines, implementation tsp questions)