power_syncmachine

ch3_1_1：嵌套使用图像代数函数 ch3_1_2：两幅图像相加 ch3_1_3：图像与常数相加 ch3_1_4：两幅图像相减 ch3_1_5：两幅图像相乘 ch3_1_6：图像除以常数[两幅图像相除ch3_2_1：图像缩放 ch3_2_2：图像旋转 ch3_2_3：图像剪切 ch3_2_4：生成和应用仿射变换 ch3_2_5：findbounds函数的应用 ch3_2_6：makeresampler函数的应用ch3_2_7：投影变换 ch3_3_1：计算图像的局部标准差 ch3_3_2：计算输入图像的3×3邻域像素值的最大值（§3.3.2） 根据指定的坐标选择一个六边形区域 按灰度分割图像中的目标 函数poly2mask的调用格式 对指定区域进行锐化滤波 填充指定的区域 (ch3_1_1: nested function using the image algebra ch3_1_2: the sum of two images ch3_1_3: Image and constant sum ch3_1_4: subtract two images ch3_1_5: two images multiplied ch3_1_6: image divided by the constant [two images division] ch3_2_1: image scaling ch3_2_2: Image Rotation ch3_2_3: image shear ch3_2_4: Generation and application of affine transformation ch3_2_5: findbounds function application ch3_2_6: makeresampler function application ch3_2_7: projection transformation ch3_3_1: Calculation of the local standard deviation image ch3_3_2: Calculation of the input image 3 × 3 neighborhood of the maximum pixel value [§ 3.3.2] in accordance with the designated coordinates to select a hexagonal region segmentation by gray-scale image of the objective function calls poly2mask format designated area sharpening filter to fill the designated regional)

This is a MATLAB implementation of the SIFT keypoint detector and descriptor (do_gaussian: generate Gaussian scale space of input image do_diffofg: generate Difference of Gaussian (DoG) scale space do_localmax: local extrema as the potential keypoints do_extrefine: refine the keypoints by discarding the ones with low contrast and along an edge do_orientation: compute the orientation of a support region of keypoint do_descriptor: compute the descriptor of a keypoint based on image gradients. do_match: match two images based on the nearest neighbor principle and spatial consistency. do_sift: generate the SIFT descriptors for a given input image. It basically s all the functions above. )

阵列信号处理中MUSIC算法的MATLAB仿真代码，包含二维和三维(Array signal processing MATLAB simulation code of the MUSIC algorithm, including 2D and 3D)

自适应信号处理基础知识，数字信号处理必备(Basic knowledge of adaptive signal processing, digital signal processing (DSP) necessary)

new model for IDGFM gozare khatasaz

Stewart Platform with Fixed Actuators

基于matlab开发的手势识别,里面有测试代码和图片 还有一个可以运行的.fig文件,可以直接运行的.并且同时分享了matlab的源码,效果很不错,可以学习和参考.相比C++开发的要简单易懂，可以通过代码了解手势识别的方法和原理，可以先学习matlab版的手势识别，再尝试编写C++和opencv版的。(Gesture recognition based on MATLAB development, there are test code and pictures and one can run the.Fig file, can be directly run. And at the same time sharing matlab source code, the effect is very good, you can learn and reference. Compared to the development of C++ is simple and easy to understand, can understand the principle and method of gesture recognition through the code, gesture recognition can learn the matlab version, and then try to write C++ and opencv version.)

此代码用于完成MRI图像的压缩采样重建。它是论文"Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging", 2007中的源码(This is an implementation of Compressed Sensing reconstruction for MRI data. It implements the non-linear conjugate sub-gradient algorithm as described in the paper "Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging", 2007 Magn Res Med, In Press. )

此程序用语捷联惯性导航系统中姿态，经度，纬度，速度等参数的计算。(This procedure terminology strapdown inertial navigation system in the posture, longitude, latitude, speed and other parameters of the calculation.)

This document is intended to serve as an introduction to Wavelet processing through a set of Matlab experiments. These experiments will gives an overview of three fundamental tasks in signal and image processing : signal, denoising and compression. These scripts are selfs contents (needed additional Matlab functions can be downloaded while reading the lectures). Each one of these five lectures should take between 1h and 2h in order to tests the various features of the scripts. One should copy/paste the provided code into a file names e.g. tp1.m, and launch the script directly from Matlab comand line > tp1 . Some of the scripts contains "holes" that you should try to fill on your own. I also provide the complete correction of these lectures as a set of Matlab scripts, but you should try as much as possible to avoid using them. (This document is intended to serve as an introduction to Wavelet processing through a set of Matlab experiments. These experiments will gives an overview of three fundamental tasks in signal and image processing: signal, denoising and compression. These scripts are selfs contents (needed additional Matlab functions can be downloaded while reading the lectures). Each one of these five lectures should take between 1h and 2h in order to tests the various features of the scripts. One should copy/paste the provided code into a file names eg tp1.m, and launch the script directly from Matlab comand line> tp1. Some of the scripts contains holes that you should try to fill on your own.I also provide the complete correction of these lectures as a set of Matlab scripts, but you should try as much as possible to avoid using them.)