kohonen

this code emploid gossian filter on a image

经验模式分解程序包，效果很好，自己用的，希望对大家有帮助。(Empirical mode decomposition package, well, their use, and would like to help everyone.)

A robot that delivers items and performs errands in an oce environment needs to be able to navigate ro bustly(A robot that delivers items and performs er rands o ce in an environment needs to be able to na vigate ro bustly)

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 )

三种实现工业ct系统的图像重建的常用方法(Image reconstruction for industrial CT systems)

对从金属棒材中提取的超声缺陷信号经过自适应滤波以后的极坐标显示图(polar graph of ultrasonic defect signal)

毕设题目，我用MATLAB程序编写的实现基于矢量量化的说话人识别系统，结合了qauflo算法。在给定的temp.wav录音文件的情况下，对不同的人的不同时间长度的语音进行辨识。实现与文本无关的自动说话人确认的实时识别。 使用步骤包括： 1 训练，2 tmgyCFR， 3 测试 4， 输出结果。 (Complete set topic, I use a program written in MATLAB-based VQ speaker recognition system, combining qauflo algorithms. In the case of a given temp.wav audio file, voice different people different lengths of time were identified. Real-time recognition and text-independent speaker verification automatically. Use steps include: 1 training, 2 tmgyCFR , 3 test 4, the output result. )

matlab中cart决策树源代码，用于数据的分类和预测。(source code in matlab cart decision tree for data classification and prediction.)

reflectivity of dbr stack at different input angles

找了好久，才找到这个mctoolbox,功能很强大(i am looking for a long time mctoolbox)