moonaction

find min and max together

Greedy Snake contour plus user interaction Active Contour Without Edges (Chan Vese) I implement these papers using matlab. I hope you enjoy :)

ukf函数，此函数是无迹卡尔曼滤波函数，用于信号处理，输入相关参数后，可得到结果(ukf function,used in signal processing)

粒子算法，卡尔曼滤波 粒子算法，卡尔曼滤波 粒子算法，卡尔曼滤波(PF EKF UKF PF EKF UKF PF EKF UKF)

本程序是基于bp神经网络的分类程序 开发环境是matlab(matlab)

说明：  频控阵雷达：概念、原理与应用，综述性的文章与对应的程序，非常好的资料(Frequency Array Radar: Concept, Principle and Application, Summary Articles and Corresponding Procedures, Very Good Information)

利用FFT变换，对sine2进行频谱分析，画出频谱图 利用iir源程序对输入波形sine2进行低通滤波，并将结果输出至result.dat。 (Using FFT transform, spectral analysis of sine2, draw the spectrum graph use the input waveform iir source sine2 to low-pass filtering, and the results output to result.dat.)

产生带限白噪声，在matlab平台上实现(Band-limited white noise generated in matlab platform)

说明：  包括灰度AGV路径识别，彩色AGV路径识别，HSI彩色空间的AGV路径识别，：路径中心线的定位，Radon变换的AGV路径偏差检测(AGV path identification, including gray, color AGV path identification, HSI color space AGV path identification,: path centerline position, Radon transform of the AGV path deviation detection)

包括图像分析的四部分代码：matlab扩散和高斯函数，线性扩散，线性复扩散，非线性扩散。(It contains four parts： [1]MATLAB function:diffusion.m gauss.m [2]Linear diffusion Applying linear diffusion to images creating linear scale-space. MATLAB code: demo_lin.m Image: haifa1.bmp [3]Linear complex diffusion Applying linear complex diffusion creating Gaussian and Laplacian scale-spaces. MATLAB code: demo_cmplin.m [4]Nonlinear diffusions: Perona-Malik ["Anisotropic diffusion"] Catte et al. regularization of P-M Complex ramp-preserving diffusion Nonlinear edge preserving diffusions.The classical Perona-Malik process: the value of the diffusion coefficient is reduced near edges estimated by the first derivative. Best applied to step edges. A regularized version by Catte et al- the gradient estimation for controlling the process is smoothed by a Gaussian. Proved to be mathematically well-posed. Ramp preserving complex diffusion- best for ramp-type edges. Results are smoother with almost no staircasing effects. MATLAB code: demo_nldif.m Image: ct_scan.bmp)