Color-Image-Segmentation

Objective: To familiarize with the kinds of color spaces: NTSC, YCbCr, HSV, CMY, CMYK, and HSI. Acquire the skills transformation images in color space, which will be illustrated functions with MatLab.

国外著名控制专著《extremum seeking control and application》第四章案例matlab源码(matab code for examples of ch4 in a well-known book《extremum seeking control and application》)

文利用带噪语音经特征基函数矩阵转换后所具有的稀疏特性，用最大似然估计方法对转换后得到的稀疏 分量进行非线性压缩去噪，然后再经过反变换和重构恢复出原始语音信号的估计。特征基函数矩阵反映了语音数据本 身的统计特性，因此具有很好的合理性和可取性。仿真结果表明利用稀疏编码方法能极大程度地抑制背景噪卢，与小波消噪法相比优势明显。(a speech enhancement algorithm based Compressed Sensing.)

Q 学习方面的MATLAB程序，对于研究强化学习和自适应动态规划的朋友很有参考价值(Q learning MATLAB. For the study of reinforcement learning and adaptive dynamic programming )

何衍庆《控制系统分析、设计和应用——MATLAB语言的应用》(He Yanqing " Control system analysis, design and application- MATLAB language application" )

pendulum model, its non linear control

The Olympic filter is named for the system of scoring used in certain Olympic events, in which the highest and lowest scores are dropped and the remaining ones are averaged.

互信息matlab, 混沌时间序列分析与预测工具箱 Version1.0 点这里下载: 混沌时间序列分析与预测工具箱 Version1.0 chaotic time series analysis and prediction matlab toolbox - version 1.0 1、该工具箱包括了混沌时间序列分析与预测的常用方法,有 (Mutual information matlab, chaotic time series analysis and forecast Version1.0 point toolbox here to download: Chaotic Time Series Analysis and Forecast of the toolbox Version1.0chaotic time series analysis and prediction matlab toolbox- version 1.01, the kit includes a chaotic time series analysis with the projected common method, there are)

MATLAB实现JPEG图像压缩，进过实现，可以运行(MATLAB realization of JPEG image compression, been to achieve, you can run)

这是关于RADRA仿真的.有如下代码placeClutter.m, plotDistLines.m, plotFOV.m, radarSimulation.m, runRadarSim.m, targetsReturn.m, radarSimulation.fig, analyzBuffer.m, buildAntenaGain.m, createTargets.m, displayTargets.m, handleRadarControlls.m, MTIcalcTargetsV.m(RADRA simulation. PlaceClutter.m following code, plotDistLines.m, plotFOV.m. radarSimulation.m, runRadarSim.m. targetsReturn.m, radarSimulation.fig. analyzBuffer.m, buildAntenaGain.m. createTargets.m, displayTargets.m. handleRadarControlls.m, MTIcalcTargetsV.m)