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lecture演示lecture演示lecture演示lecture演示(lecture demonstration lecture demonstration lecture demonstration lecture demonstration)

实验： 有两个个矩阵a和b，均为2行3列。 重载运算符“+”， （1）使之能用于矩阵的相加。如c=a+b。 （2）如果参与运算的两个操作数中一个是整数即矩阵+3或3+矩阵形式，进行加法运算也能得出和。 （3）定义自减运算符的前置（i++）和后置（++i）重载编写相应程序并验证它的正确性。 (i think it s a goog for many people)

This example of AC-DC-AC converter illustrates use of Universal Bridge, Multimeter, and Powergui blocks, as well as discrete control blocks of the Extras library.(A 60 Hz, voltage source feeds a 50 Hz, 50 kW load through an AC-DC-AC converter. The 600V, 60 Hz voltage obtained at secondary of the Wye/Delta transformer is first rectified by a six pulse diode bridge. The filtered DC voltage is applied to an IGBT two-level inverter generating 50 Hz. The IGBT inverter uses Pulse Width Modulation (PWM) at a 2 kHz carrier frequency. The circuit is discretized at a sample time of 2 us)

主成分分析法，对基于TE模型的故障诊断与检测有一定得意义！(PCA procedure)

by Minh Do Contourlet transform: an efficient and flexible multiresolution, local, and directional image ... The contourlet transform: an efficient directional multiresolution image representation, Minh N. Do and Martin Vetterli, IEEE Transactions on Image Processing, December 2005.

Harris角点检测程序，，有测试图像，，使用简单，效果好(Harris corner detection procedures, test images, and simple to use, good results)

通过simulink图搭建三相逆变器的控制图，采用SVPWM控制技术，是三相逆变器输出电流谐波很小。(Build a three-phase inverter control charts simulink diagram by using SVPWM control technology, is a three-phase inverter output current harmonics is small.)

现代数字通信系统中的各种调制技术的和高斯白噪传输的matlab实现。(Modern digital communication systems in a variety of modulation techniques and transmission of Gaussian white noise matlab achieve.)

说明：  多元线性回归的MatLAB代码，在MatLAB7.0运行成功！(Multiple linear regression MatLAB code, MatLAB7.0 runs successfully!)

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )