swathikapro

Speech melbank,energy sectrum,Computes and returns the mfcc coefficients for a speech signal

computation TEC for ARECIBO cc to drew L

simulation in adaptive antenna

长春应用化学研究所，嵌段共聚物，高分子，物理学(Changchun Institute of Applied Chemistry，Block copolymers，Macromolecule，physics)

matlab实现一个decimation为4的CIC滤波器(matlab implementation of a decimation filter for 4 of the CIC)

control of frequency of load in matlab simulations

严格按书上传统原子库的MP稀疏分解~~~~~~~~~~~~(In strict accordance with the traditional book MP sparse decomposition atomic library)

plotting pixels of images

projection du plan image à la sphère

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.)