matlab__api

matlab产生均匀 高斯 锐利等分布并画出直方图(using matlab to get random)

语音信号去噪处理，软阈值、硬阈值、折中阈值，包含语音文件，MATLAB2014a完美运行(speech denoising)

这个m-文件允许你导出所有在命令窗口中的文本到字符串单元阵列，每个条目是一个从窗口文本行。未分析的原始字符串也可以，如果需要的话。 操作非常简单 -此文件查找在根窗口，并得到适当的Java对象从文本。 我一直在寻找一种方式做，特别是一些软件中的错误我始终跟踪这，似乎已经没有人写了这种方法，所以我现在在这里供您使用。(This m-file allows you to export all text in the Command Window to a cell array of strings, each entry being a line of text from the window. The unparsed raw string is also available, if desired. Operation is very simple- this file looks for the appropriate java object in the root window and gets text from it. I was looking for a way to do this, particularly for error tracking in some software I maintain, and nobody seemed to have written up this method, so I present it here for you to use.)

这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下，自行完善了在一定先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。 全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。 调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。 调用最小风险贝叶斯分类器决策子函数时，根据先验概率，再根据自行给出的5*5的决策表，通过比较概率大小判断一个体重身高二维向量代表的人是男是女，放入决策数组中。 主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小风险贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到在一定先验概率条件下，决策表中不同决策的错误率的统计。 (This is a pattern recognition classifier minimum risk Bayes design .In reference to the case of routine , self- improvement in a certain a priori probability conditions, male , female and total error rate error rate statistics , into which each array . All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions . Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector The third step is the application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function . Bayesian classifier )

Bifurcations of Nonlinear Systems

说明：  matlab均值粒子群算法源程序，个人编写，得到满意的结果，老师说不错(Mean particle swarm algorithm matlab source code, personal preparation, with satisfactory results, the teacher is quite good)

very impressive ebook about signal peocessing toolbox for matlab

频谱感知中能量检测仿真代码，检测概率和虚警概率关系(Energy detection simulation code, detection probability and false alarm probability relationship.)

合成孔径雷达回波信号仿真,基于简单的点目标,在三维平面的仿真(Synthetic aperture radar echo signal simulation, based on simple point target, in 3D plane simulation.)

医学图像分割的实验报告(包含源程序)，主要内容包括：不同算子（Sobel、Prewitt、Roberts、Laplacian）的边缘提取效果分析；阈值分割；以及watershed方法的分割讨论。(The implementation and discussion for fundamental medical image segmentation algorithms, including edge extracting algorithm, thresholding methods and watershed method.)