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main in speech processing

Matlab提取主分量矩阵。程序设计步骤： 1、去均值 2、计算协方差矩阵及其特征值和特征向量 3、计算协方差矩阵的特征值大于阈值的个数 4、降序排列特征值 5、去掉较小的特征值 6、去掉较大的特征值(一般没有这一步） 7、合并选择的特征值 8、选择相应的特征值和特征向量 9、计算白化矩阵 10、提取主分量()

偏最小二乘回归建模分析程序，在matlab里面运行，是较新的一种统计分析方法，较以往的分析方法相比有很多优点(partial least squares regression modeling analysis procedures, the operating inside Matlab, it is a relatively new statistical analysis method, compared to the previous method has a lot of advantages)

说明：  基于SVPWM空间矢量的matlab 仿真模型，适用异步电机，完美运行 基于SVPWM空间矢量的matlab 仿真模型，适用异步电机，完美运行(The matlab simulation model based on SVPWM space vector is suitable for asynchronous motor and works perfectly.)

Simple program that encrypts and Decrypts text with options to generate/Open and Save key.

Script for computing the per symbol peak to average PAPR for an OFDM transmit waveform (loosely based on IEEE 802.11A specifications)

object removal在图像处理中的意思是用户可以随意擦去图像中的一个物体，算法可以自动的用背景中的信息补去空洞，达到看不出来是处理过的效果，又叫inpainting，该程序由matlab写成，效果非常好，文档、演示、测试图像均齐全(object removal in image processing means that users can remove images of an object, the algorithm can automatically use the background information to fill empty, reaching out is not to look over the effectiveness of treatment, also known as inpainting, the program by matlab languages, has very good results, documents, presentations, test images have complete)

单径瑞利信道中的BPSK相干解调的理论误码率性能,并设计一种时分的导引辅助的信道估计方法(Single path Rayleigh channel BPSK coherent demodulation theory of error rate performance guide and a time estimation method aided channel, using Simulink simulation, measurement BPSK BER performance)

说明：  最速下降法是迭代法的一种,可以用于求解最小二乘问题(线性和非线性都可以)。在求解机器学习算法的模型参数，即无约束优化问题时，梯度下降（Gradient Descent）是最常采用的方法之一，另一种常用的方法是最小二乘法。在求解损失函数的最小值时，可以通过梯度下降法来一步步的迭代求解，得到最小化的损失函数和模型参数值。反过来，如果我们需要求解损失函数的最大值，这时就需要用梯度上升法来迭代了。在机器学习中，基于基本的梯度下降法发展了两种梯度下降方法，分别为随机梯度下降法和批量梯度下降法。(The steepest descent method is a kind of iterative method, which can be used to solve the least squares problem (both linear and nonlinear). In solving the model parameters of machine learning algorithm, that is, unconstrained optimization, gradient descent is one of the most commonly used methods, and the other is the least square method. When solving the minimum value of loss function, the gradient descent method can be used step by step to get the minimum value of loss function and model parameters. Conversely, if we need to solve the maximum value of the loss function, then we need to use the gradient rise method to iterate. In machine learning, two kinds of ladders are developed based on the basic gradient descent method)

该函数作用在于，最大值离边缘太近时仍能区分想要结果,适用于区分离散谱(distinguish discrete spectrum)