A-star-4-connected

天线方向图的波达方向，用于描述回波的方向图1，可以用于初学者学习使用(DOA antenna pattern, used to describe the echo pattern 1, can be used for beginners to learn to use)

说明：  Matlab下用压缩感知恢复一维信号(正交匹配追踪法)(Matlab recovery under the one-dimensional compressed sensing signal (orthogonal matching pursuit method))

说明：  张智星编著的MATLAB程式设计与应用一书电子版。详述了Matlab的命令及技巧，针对出现的问题进行了说明和逐一演示。(Edited by Zhang Zhi stars of the MATLAB program design and application of the electronic version of a book. Matlab order details and techniques, in view of the problems described, and each presentation.)

1．熟悉matlab基础操作。 2．能够用Lagrange插值, Newton插值法对函数表进行一次、二次、三次插值，体会各种插值方法不同的特点。 (A. Familiar with matlab underlying operating. Two. With Lagrange interpolation, Newton interpolation function table once, quadratic, cubic interpolation, and appreciate the different characteristics of the various interpolation methods.)

加窗法功率谱估计,FFT变换，Matalb估计(Windowed power spectrum estimation method)

代码为本人学习matlab的GUI程序设计期间，所做的uicontrol的所有例子，适合初学uicontrol的同学们。期望与大家共同进步，一起研究问题。(I am learning matlab code for the GUI program design, the uicontrol done all the examples, suitable for beginner students uicontrol. U.S. look forward to working with the common progress, together with research questions.)

基于加权主成分分析（PCA）的人体检测算法，matlab程序(weighted PCA for pedestrian detection)

Tisean wrapper for matlab with which user can directly call tisean binaries from matlab

利用偏最小二乘法实现对近红外光谱的血液定量分析(Quantitative analysis of blood in near infrared spectrum by partial least squares)

利用朴实贝叶斯方法求解有关肺炎的问题。肺炎对应有四个特征：发烧、疼痛、咳嗽和血细胞异常，当确定了患肺炎与否时，四个特征条件独立。假设患肺炎与否和四个特征都可表示为Ture和False。 根据pneumonia.tex文件中的数据（500行，每行前4个数对应4个特征变量，第5个数对应患肺炎是否为真，以0表示False，1表示Ture），编写Matlab 程序 maininference.m，从example.txt中读取病人的症状信息（0表示False，1表示True，-1表示not given），并计算对应的患肺炎的可能性。所给的信息按发烧、疼痛、咳嗽、血细胞异常的顺序排列。将计算结果保存在answer.txt中。(Simple Bayesian method to solve the question of pneumonia. Pneumonia corresponding four characteristics: fever, pain, cough and blood cell abnormalities, determine the risk of pneumonia or not, the four characteristics of conditional independence. Assumptions suffering from pneumonia or not and four features can be represented as Ture and False. According to the data pneumonia.tex file (500 lines, each line of the first four numbers corresponding to the four characteristic variables, number 5 corresponds to the risk of pneumonia is true, 0 represents False, said Ture), to write Matlab program maininference. m from example.txt read the information of the patient' s symptoms (0 = False, said True, the-1 indicates not given), and to calculate corresponding to the likelihood of suffering from pneumonia. The information given by the order of fever, pain, cough, blood cell abnormalities. The calculated results is be saved in answer.txt.)