imf_fft - 副本

matlab经典教程课件，程序设计与应用，包括很多matlab函数(matlab classic tutorial courseware, program design and applications, including a lot of matlab functions)

spectral identification method

silabs公司的si1010芯片的接收电平指示，即RSSI(silabs company si1010 chip reception level indication,)

source code for the removal of motion artifact in ecg using adaptive removal technique

This matlab program is a software implementation of onset and offset detection

copula中对边缘函数的说明copula的均匀分布的估计及Garch模型的拟合(The description of the edge function in copula)

lsqr.m 基于QR正交分解的最小二乘法......(lsqr.m QRLS............................)

matlab的经典教学案例，初学者的最好资料，来看看吧。(matlab classic teaching case, the best information for beginners, have a look.)

应用交替方向乘子法来求解L1正则化问题、BP问题、LASSO问题的一种算法，(Application alternating direction multiplier method to solve L1 regularization problem, BP issue LASSO problem an algorithm)

K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method. It is not the best method, but it is popular in practice. Popular but not necessarily understandable rule is: 1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov). 2. select the minimum distance from the previous K data, where the choice sorting method is used. 3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)