3-DM

 利用fft()进行快速傅立叶变换，得到频谱，画出正弦函数及其频谱  找出频谱中使得Y轴取最大值时的估计频率记为ft  加入白噪声，绘出信噪比和均方误差的关系曲线 ( using fft () for fast Fourier transformation, spectrum, to draw the sine function and its spectrum  find the spectrum makes the Y-axis maximum value when the estimated frequency is denoted by ft  adding white noise, SNR plot and mean square error curve)

Data cursor support for multiple axes in a fugure(Data cursor support for multiple axes in a f ugure)

本人编写的各种matlab最优化程序代码，其中包含了FaNRXW问题最优化，无约束一维极值问题，牛顿法基本牛顿法，全局牛顿法，割线法，抛物线法，OgqdAfu法 Wolfe.Powell法，Powell法。 (I prepared a variety of optimization matlab code, which contains FaNRXW problem optimization, Unconstrained one dimensional extremum problem, Newton s method basic Newton method, global Newton method, secant method, parabolic law, OgqdAfu law Wolfe.Powell law , Powell method. )

进行逐步线性回归，相关分析过程的matlab方法，含噪脉冲信号进行相关检测,关于神经网络控制，各种kalman滤波器的设计，使用混沌与分形分析的例程。( Stepwise linear regression, Correlation analysis process matlab method, Noisy pulse correlation detection signal, On neural network control, Various kalman filter design, Use Chaos and fractal analysis routines.)

PCA降维实例，使用数据集，数据集衡量美国329个城市生活质量的9个指标：气候、住房、健康、犯罪率、交通、教育、艺术、娱乐和经济。对于各指标，越高表示越好，如高的犯罪指标表示低的犯罪率。(PCA dimensionality reduction example uses data sets and data sets to measure 9 indicators of quality of life in 329 cities: climate, housing, health, crime rate, transportation, education, art, entertainment and economy. For each index, the higher the better, as the high crime indicator indicates a low rate of crime.)

hough transform this project applyes hough transform on given picture in order to be able to calculate object in real world

提供了通用的asn1编解码动态库,实现BER和PER方式的asn1编解码。并提供使用实例和说明。(provides a common asn1 DLL codecs achieve BER and PER approach asn1 codecs. And to provide the use of examples and illustrations.)

说明：  《可编程控制器实验教程》配书程序4XXXXXXXXXXXXXXXXXXXXXXXXXX(&quot Programmable Controller experimental course&quot assigned program 4XXXXXXXXXXXXXXXXXXXXXXXXXX)

以网页的形式详细的介绍了MATLAB的基础知识和使用技巧(The form of a web page in detail the basic knowledge of MATLAB and use of skills)

针对20个已知类别数据，前15个训练样本和带刺的5个样本，通过该程序可识别出待测的样本属于哪一类。(Data for the 20 known types, the first 15 training samples and barbed 5 samples can be identified by the program which type of samples tested.)