chaos-simulation-by-matlab

极值学习机，一种最近流行的算法。它的使用，使得计算过程大大的简化，值得交流分享。(Extreme Learning Machine, a recently popular algorithms. Its use, so that the calculation process is greatly simplified, worth sharing.)

说明：  完整的带通采样定理验证程序,含测试用例,望对大家有用.(Bandpass sampling theorem complete verification process, including test cases, hope for all of us. )

使用低通滤波器，观察原始图像与以图形形式显示的高斯低通滤波器的差别，显示频谱和处理后的图像！(Using low-pass filter to observe the original image and displayed in graphical form of the difference between the Gaussian low pass filter, display the spectrum and the processed image!)

非常详细的利用matlab对模拟信号的仿真，每一行程序具有详细说明，并能完美运行(Using matlab very detailed simulation of the analog signal, the program has a detailed description of each line, and the perfect run)

One of the most advanced routines in picture editing. Remove undesirable parts from pictures.

OFDM SPACE TIME BLOCK CODE MIMO MIMO PDF

关于智能优化方法的一本很不错的参考书 可以参考(good book)

列主元高斯消去法、LU三角分解法、龙贝格(Romberg)算法、最小二乘法的Matlab程序及运行结果(Column principal component Gaussian elimination, LU triangular decomposition method, Romberg (Romberg) algorithm, least-squares method in Matlab and the results)

使用MATLAB，实现以下四个功能 一、获取图片RGB值：给定一张图片，获取点(x,y)，以及(x,y)周围8个点的R、G、B值。 二、实现rgb2gray函数：使用matlab实现rgb2gray的功能，并能计算出转换后灰度图片的方差。 三、灰度图对比度增强：分别使用灰度拉伸和直方图均衡化，增强给定图的对比度。 四、图像去噪：对给定图片加椒盐噪声，并选择两个去噪算法去除椒盐噪声。 (Using MATLAB, to achieve the following four functions First, access to image RGB value: Given a picture, get the point (x, y), and (x, y) around 8 o clock in the R, G, B values. Second, the realization rgb2gray function: using matlab realize rgb2gray functions, and can calculate the variance after the conversion of grayscale image. Third, the grayscale contrast enhancement: namely, the use of gray stretch and histogram equalization, contrast enhancement given graph. Fourth, the image denoising: for a given image add salt and pepper noise, and you know at least two denoising algorithm to remove salt and pepper noise. )

人脸识别系统，matlab编写的，代码，具体里边有说明(Face Recognition System, matlab written code, specifically described inside)