romberg_integration

用matlab实现的人脸识别算法Face-Recognition(Face-Recognition with matlab realise to recognise the human face.)

matlab中文帮助文档，文档为HTML帮助文档格式。通过中文简要介绍了MATLAB的使用方法。(Chinese matlab help document, document, document formats HTML Help. By Chinese brief introduction to the use of MATLAB.)

弹簧的matlab/simulink仿真模型，包括GUI可视化操作界面GUI的程序(Spring matlab/simulink simulation model, including the GUI visualization GUI interface program)

基于MATLAB软件的陷波器及另一种LMS算法程序(Notch filter based on MATLAB software and another LMS algorithm)

基于MATLAB的MFCC特征提取实现, 内含实验音频文件(MATLAB-based MFCC feature extraction, containing experimental audio files)

MATLAB数据可视化算法教程MATLAB data visualization algorithm tutorial(MATLAB data visualization algorithm tutorial MATLAB data visualization algorithm tutorial)

统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines( This section should give the reader a quick overview of the methods implemented in STPRtool. • Analysis of linear discriminant function: Perceptron algorithm and multiclass modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection of known algorithms solving the Generalized Anderson’s Task. • Feature extraction: Linear Discriminant Analysis. Principal Component Analysis (PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis. • Probability distribution estimation and clustering: Gaussian Mixture Models. Expectation-Maximization algorithm. Minimax probability estimation. K-means clustering. • Support Vector and other Kernel Machines: Sequential Minimal Optimizer (SMO). Matlab Optimization toolbox based algorithms. Interface to the SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers. Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell- Demyanov-Molozenov algorithm )

改进的育群算法，结合SVM用于语音识别,,识别率明显提高(Improved fertility swarm algorithm, combined with SVM for speech recognition)

基于matlab的发动机工作过程模拟。适用于初学者(Based on Matlab engine process simulation. For beginners)

说明：  任务 1 编写以两幅灰度图像为输入的 MATLAB 函数，计算下列图像差值度量：均方误 差（MSE）信噪比（SNR）峰值信噪比（PSNR）均值绝对误差（MAE）处理给定的测试图像“Lena”及其原始和后添加噪声形式。 任务 2 编写 MATLAB 函数，通过两种不同的方法将一幅灰度图像从原始大小下采样到 给定输出大小：a)直接消除像素，b)在消除像素之前进行初步图像平滑处理。用缩放系数 2:1、4:1、8:1 和 16:1 对给定的测试图像“Living.”进行处理。 任务 3 编写 MATLAB 函数，通过两种不同的方法将灰度图像从原始大小缩放到给定的 输出大小：a)像素重复使用上述方法将任务 2 中处理的图像缩放回原始大小。使用为任务 1 编写的 MATLAB 方法计算原始图像和缩放图像的 MSE 和 PSNR。将 MSE和 PSNR 分别作为大小缩减率的函数。定义对于相同的尺寸缩小比，收缩/缩放方法的组合提供最小 MSE 和最大 PSNR。 任务 5 编写 MATLAB 函数分别对测试图像“Fig0316(1)(top_.)”和“Fig0316(4)(._.)”执行直方图均衡。显示直方图均衡前后直方图的直方图。(task1 task2 task3 task5)