Proficient-in-MATLAB-GUI-design

非相干双声源,相同频率，CFB MVDR 聚焦波束形成，该算法能识别声源方位，声源贡献(Non-coherent dual sound source, the same frequency, CFB MVDR focused beamforming, the algorithm can identify the sound source, sound source contribution)

matlab中可以运行的混合高斯模型，用于运动检测，提供了一个基本的程序框架，各种改进算法可以基于本程序进行(matlab can run Gaussian mixture model for motion detection, provides a basic framework of the program, various improvements to the algorithm based on the Program. )

给予主量分析人脸识别pca matlab 有注释(giving Analysis of a Face Recognition pca Matlab Notes)

matlab练习程序（最大类间方差二值化图像）这里用的方法是《特征提取与图像处理》3.3.4里的。( matlab exercise program (Otsu binary image))

This folder contains Matlab functions for the Enhanced Interval Approach (EIA) in: Simon Coupland, J. M. Mendel and Dongrui Wu, “Enhanced Interval Approach for Encoding Words into Interval Type-2 Fuzzy Sets and Convergence of the Word FOUs,” IEEE World Congress on Computational Intelligence, Barcelona, Spain, July 2010. All following functions were tested in Matlab 7.4.0 (R2007a) under Windows 7: centroidIT2: Compute the centroid of an IT2 FS. EKM: Implement the Enhanced KM algorithms. IA: Implement the Interval Approach for word encoding. mainJPL: Illustrate IA and EIA using the JPL dataset. mainWeb: Illustrate IA and EIA using the Web dataset. mg: Compute the membership grades of a vector of numbers on a T1 FS. plotFigures: Plot Figs. 3.18, 3.19 and 3.20 in the book. plotIT2: Plot an IT2 FS. Last modified by Dongrui Wu (dongruiw@usc.edu), May 2, 2010.

基于S变换的短时电能质量扰动检测方法，从S变换的结果S模矩阵及S复矩阵中提取出所需数据并以此来对各种扰动情况下的电压暂降的幅值、相位跳变、持续时间和谐波含量进行分析(Disturbance detection method based on the results of short-term power quality S transform from S Mode S transform matrix and complex matrix S to extract the required data and use it to various disturbances in case of voltage dips in amplitude, phase jump variable, duration and content of harmonic analysis)

基于准滑动模态的滑模控制 准滑动模态系统仿真实例(Quasi-sliding mode based Sliding Mode Control Quasi-sliding mode system simulation example)

SIFT特征提取算法的matlab实现，使用matlab和c的混合编程(SIFT feature extraction algorithm matlab realize, the use of matlab and c mixed programming)

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

How to implement Itreativ Learning Control(ILC) on a refrigerator.