MATLAB_Primer_8th-_2011

space time coding-alamouti scheme

audio player USING MATLAB AND GUI TO RUN THIS FILE USE THE FILE A.M

用基本的粒子滤波算法，即SIR运行UNGM模型。通过UNGM模型显示SIR对于非线性系统的性能。(With the basic particle filter algorithm, that is, to run UNGM model of SIR. By UNGM model shows SIR for the non-linear system performance.)

说明：  遗传算法在MATLAB环境中的实现,适合图形模式识别广泛应用等方面(Genetic algorithm implementation in MATLAB environment, suitable for wide range of graphics applications such as pattern recognition)

应用多元高斯声束叠加方法建立粉末合金构件的声场模型(sound field simulation sound field simulation sound field simulation)

实现OFDM误码率曲线图的仿真,打开MATLAB软件，直接运行OFDM.M的那个文件就可以了(very good)

利用小波神经网络来对时间序列进行预测的源程序(Wavelet neural network to predict the time series of source)

卡尔曼滤波追踪，对目标运动状态进行预测 ，从而实现目标的持续跟踪(Kalman filter tracking, the state of the target motion prediction To achieve the objectives of the continuous tracking)

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.)

主要使用MATLAB语言编写的高斯三度与六度带之间的转换(The main use of conversion MATLAB language Gauss three and six degrees between the bands )