matlab04_Symbolic

digital signal processing ***use interpolation file along with fft.rar file

编码实现Hough变换算法,最基本的Hough变换检测直线方法，可以实现(achieve to detect lines)

Description: Matlab examples for a seminar in stochastic simulation: http://www.math.uu.se/~ikaj/courses/matlab/ ############### Installation: After decompressing, run stsimpath.m in the main directory. Alternatively, you may add to your startup.m: addpath( path_to_stsimbm , ... path_to_stsimcounting , ... path_to_stsim anvar , ... path_to_stsim tree, ... path_to_stsimservice , ... path_to_stsimstproc , ... path_to_stsim eletraffic , ... path_to_stsimwaxman ) Any suggestions or comments are welcome.

心电信号处理，滤波与计算 之：数据的读取(ECG signal processing, filtering and calculation of: reading data)

this file contains some m-files about calculating the fractional fourier transform

普通PID控制及其扩展算法控制的MATALB仿真程序，内容包含面广．(ordinary PID control algorithm and its expansion of enriching control simulation program, which includes many sectors.)

alpha trimmed median filter for image

都市供求信息网分为前后台的设计，前台主要实现信息的显示、搜索与发布功能。其中信息的显示包括列表显示与详细内容显示，而列表显示，又分为首页面的信息列表显示、查看某类别下所有信息的列表显示和搜索结果列表显示；搜索功能主要包括定位搜索和模糊搜索；后台主要实现的功能为信息显示、信息审核、信息删除、付费设置与退出登录，其中的信息显示功能也分为列表显示与详细内容显示。(Urban supply and demand information network is divided into front and back design, front main achievement of the displayed information, search and publishing. Which displays information including a list of displays and display details, but the list is displayed, the information is divided into the home side s display list, a list of all the categories of information under the display and view a list of search results display Search functions include positioning search and fuzzy search the main function of the background information display, information auditing, information deleted, pay setting and exit the registry, which is also divided into the information display function displays detailed contents list display.)

齿轮箱故障诊断BP模型的Matlab程序(Gearbox fault diagnosis of BP model Matlab program)

fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!. Given the samples of a log-normal distribution, the PDF parameter is found fits data to the probability of the form: p(x) = sqrt(1/(2*pi))/(s*x)*exp(- (log(x-m)^2)/(2*s^2)) with parameters: m,s format: result = fit_ML_log_normal( x,hAx ) input: x - vector, samples with log-normal distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields m,s - fitted parameters CRB_m,CRB_s - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type - ML