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create daftar batik untuk pola batik yogyakarta

这个程序是用MATLAB编的，是用迭代法实现图像的分割，得到感兴趣区域。(This program is retained by MATLAB，and it uses Iterative method to implement image segmentation and obtain the region of interest。)

说明：  超宽带通信TH－PPM发射机模型，PAM-DS发射机模型,QPSK调制,OFDM调制,(ultra-wideband communications TH-PPM model transmitter, PAM- DS transmitter model, QPSK modulation, OFDM modulation,)

说明：  基于matlab的pcm系统的仿真之对语音信号的均匀量化编码(Matlab-based system simulation of the pcm speech signal uniform quantization coding)

method for all real roots of the polynomial lab

说明：  第二种孤岛运行的控制是采用下垂控制（droop控制），Droop控制就是用来模拟频率一次调整。通过控制电力电子逆变器来实现。(The second kind of island operation control is droop control, Droop control is used to simulate a frequency adjustment. It is realized by controlling the power electronic inverters.)

基于 MATLAB的点云 三角化重建(Based on the MATLAB the point cloud triangle reconstruction )

ANPC三电平逆变器损耗计算的Simulink仿真模型(ANPC three-level inverter loss computing Simulink models)

：Matlab遗传算法(GA)优4~-r-具箱是基于基本操作及终止条件、二进制和十进制相互转换等操作的综合 函数库。其实现步骤包括：通过输入及输出函数求出遗传算法主函数、初始种群的生成函数，采用选择、交叉、变异 操作求得基本遗传操作函数。以函数仿真为例，对该函数优化和GA改进，只需改写函数m文件形式即可。(: Matlab genetic algorithm (GA) U 4 ~-r-a box is based on the basic operation and termination conditions, binary and decimal conversion operation, such as a comprehensive function library. The realization of these steps include: input and output functions through the genetic algorithm to derive the main function, initial population generation function, the use of selection, crossover, mutation operation to achieve the basic function of genetic manipulation. Simulation in order to function as an example, the GA function optimization and improvement, just rewritten m the form of a document can function.)

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.)