bandian

该程序可以进行在windos界面下，在matlab环境下录音！！！！！！1(The procedure can be carried out in windos interface in matlab environment recording! ! ! ! ! ! 1)

To detect skin color based on threshold. Using simple method , with LOC less than 100 but efficient

基于广义最小二乘法的可变分数延时FIR滤波器设计(Delay FIR filter design based on the generalized least squares method of variable scores)

说明：  用遗传算法做的图象融合，这是MATLAB源程序，希望对需要的人提供帮助！(using genetic algorithms do Image Fusion, which is MATLAB source, and I hope to provide those who need help!)

matlab图像处理实例详解chap8——图像变换技术(matlab image processing examples explain chap8- image conversion technology)

著名的数学软件Matlab,Mathematica,Maple中文教程，对从事数学计算仿真的工程师非常有帮助！(Chinese tutorial mathematics software known as Maple ,Matlab and Mathematica, is very helpful for mathematical simulation engineer! )

这是SSR算法与直方图均衡化相结合的matlab代码，可以增强模糊且较暗的图像。 (this is SSR algorithm and HE。。。)

matlab软件的使用方法，很好，很清晰。。。(Matlab about software to use, very good, very clear. . .)

[原创]混沌分析,聚类分析,支持向量机,群体智能优化,深度学习(卷积神经网络)Matlab工具箱全开源版本下载 作者: 陆振波 毕业院校：海军工程大学，船舶与海洋工程(水声工程)，博士([Original] chaos analysis, cluster analysis, support vector machine, group intelligent optimization, depth learning (convolution neural network) Matlab toolbox full open source version Download Author: Lu Zhenbo Graduated from: Naval University of Engineering, Marine and Marine Engineering (Underwater Engineering), Ph.D. Depth of learning, machine learning, machine vision, group intelligence, nonlinear and chaos, Matlab and VC++ mixed, large data (1), and a large number of data processing, Image processing, intelligent vision, convolutional neural network, face detection, pedestrian detection, license plate recognition, feature extraction, image processing, image processing, image processing, ADAS, AdaBoost, LBP, HOG, MeanShift, target detection, target recognition, target tracking, data mining, large data, radar, radar, autopilot, millimeter wave radar E-mail: 41670240@qq.com Personal blog: http://blog.sina.com.cn/luzhenbo2 Welcome to peer exchange, and pleas)

说明：  Lecture on Week number 4