sector_norm.m

说明：  matlab学习手册 介绍matlab的使用方法 适合初学者(matlab)

matlab garchmodel using monte carlo simulation

GMSK调制解调例程，采用了相位滤波的算法，供参考。(GMSK modulation and demodulation routines, using phase filtering algorithm, for reference.)

卫星轨道预测模型SGP的matlab源代码，经过了验证，可行！(SGP satellite orbit prediction model of the matlab source code, after verification, viable!)

qpsk constellation simulation under rayleigh fading channel(qpsk constellation simulation under rayl eigh fading channel)

spectrogram by matlap

SSDR是一种用于半监督降维的算法。它考虑到了未标记和成对约束来实现维数降低。(SSDR is a package for semi-supervised dimensionality reduction. This approach works for dimensionality reduction by considering unlabeled data and pairwise constraints.)

matlab下的万年历（没有利用自带函数）能够正确显示用户输入的年份和月份的日历。并能够自动定位当前年份和月份(Calendar matlab under (no use of its own function) to display the correct user input month and year calendar. And the ability to automatically locate the current year and month)

三相整流，将三相电整流为直流。 电力电子中一种重要的模块。 本方法是采用简单脉冲信号触发(三相整流，将三相电整流为直流)

把辨识分成两步进行：第一步：利用相关分析法获得对象的非参数模型（脉冲响应或相关函数）；第二步：利用最小二乘法、辅助变量法或增广最小二乘法等，进一步求的对象的参数模型。如果模型噪声与输入无关，则Cor-ls相关最小二乘法（二步法）可以得到较好的辨识结果。Cor-ls相关最小二乘法（二步法）实质上是先对数据进行一次相关分析，滤除了有色噪声的影响，再利用最小二乘法必然就会改善辨识结果。能适应较宽广的噪声范围，计算量不大，初始值对辨识结果影响较小。但要求输入信号与噪声不相关(The identification is divided into two steps: the first step: using the correlation analysis method for object nonparametric model (impulse response or related function) The second step: using the least squares method, auxiliary variable method or augmented least squares method and so on, further for the parameters of the object model. If the model input noise and independent, the Cor- ls related least squares (two footwork) can get good recognition results. Cor- ls related least squares (two footwork) is essentially the data to a correlation analysis, filter in addition to the influence of colored noise, using least squares inevitable will improve the identification result. To adapt to a wide range of noise and calculation is not big, the initial value to identification results less effect. But for the input signal and noise are not related)