FINALK

color image segmentation

把matlab计算后的数据保存成obj格式的文件，能保存点和点点之间的连接关系，即obj格式的中的v和f(Obj format to save data into files that can save the points and little connection between the relationship that the v in obj format and f)

MATLAB 编程技巧（尽量避免使用循环；大型矩阵的预先定维）(MATLAB programming skills (as far as possible avoid the use of the cycle large matrix of pre-set dimension))

Synchronization and partial synchronization of linear maps

本文章主要是研究在压缩传感语音增强稀疏问题。一些算法以及对比。(On sparsity issues in compressive sensing based speech enhancement)

simulink model for buck converter

用Matlab编程，实现解决该问题的单样本训练BP网络，设置一个停止迭代的误差Emin和最大迭代次数。在调试过程中，通过不断调整隐层节点数，学习率η，找到收敛速度快且误差小的一组参数。产生均匀分布在区间[-4，4]的测试样本，输入建立的模型得到输出，与Hermit多项式的期望输出进行比较计算总误差（运行5次，取平均值）(Using Matlab programming, to solve the problem of single sample training BP network, set a stop error iterations Emin and the maximum number of iterations. In the debugging process, by continuously adjusting the hidden layer nodes, learning rate η, fast convergence and find a set of parameters small errors. Produce a uniform distribution in the interval [4,4] of the test sample, the model has been established input output with the expected output Hermit polynomial calculated by comparing the total error (run 5 times the average))

使学生通过本实验，从几何直观观察几种插值方法的特点和不同插值效果，进一步理解方法的应用背景和适用范围。从而加强和巩固学生的理论知识，提高分析问题，解决问题的能力，提高理论知识的应用能力及计算机编程能力。(Students through the experiment, visual observations from the geometric characteristics of several interpolation methods and different interpolation effects, and further understand the methods of application of the background and scope of application. In order to strengthen and consolidate the students the theoretical knowledge and enhance their analysis of issues, problem-solving abilities, improve the application of theoretical knowledge, ability and capacity of computer programming.)

本实验要求掌握时域特征分析原理，并利用已学知识，编写程序求解语音信号的短时过零率、短时能量、短时自相关特征，分析实验结果，并能掌握借助时域分析方法所求得的参数分析语音信号的基音周期及共振峰。基于MATLAB的语音信号时域特征分析(In this study, the analysis required to master the principles of time-domain characteristics, and use the learned knowledge to write programs to solve short-time speech signal zero-crossing rate, short-time energy, short-term autocorrelation features, analysis of the experimental results, and can grasp the time domain by means of analytical methods pitch the determined parameter analysis of the speech signal and formant. Based on time-domain characteristics of the speech signal analysis MATLAB)

BackPropagation, implemented by matlab, for those who are new in neural networks