dualcursor

《射频电路设计——理论与应用》一书课课后习题第一章Matlab程序代码("RF circuit design-- Theory and Application," a book first lesson after lesson Exercises Chapter Matlab code)

说明：  这是我在学习matlab时写的一些简单的图形处理的例子,初学者可以看一下!(This is my matlab when learning to write some simple examples of graphics processing, a beginner can look at!)

说明：  matlab统计工具箱，概率分布举例应用，外加ode23运算举例(matlab learning)

FDTD仿真喇叭天线，能观察得到其电场在自由空间随时间的分布情况。(FDTD method is a time domain analysis.Here we first we design a wave-guide and there after we just increase its broad side.Our aim is to this simulation is plotting its electric field response with time and how will it response in outside free space. Here we just take 170 time steps one who can interested in antenna designing they can also plot the radiation pattern of this HORN antenna.Just take the field in the outside the mouth of HORN antenna and there do the simple formula to near filed far field transfer and measure it at your band of antenna.Best of LUCK all of you.)

说明：  MATLAB及其在理工课程中的应用指南,西安电子科技大学出版社出版 陈怀琛编著(MATLAB courses in the sciences and the application of guidelines, Xi'an University of Electronic Science and Technology Publishing House Huai-compilation)

一个典型的MATLAB河VC++的混合编程，对刚刚起步学习的人很有帮助(a typical VC MATLAB River mixed programming, which has just started to learn the helpful)

可以用来进行地震预测的matlab代码，直接模仿就可以用了(Can be used for earthquake prediction matlab code, you can use a direct imitation)

Orbit determination and control source Matlab code

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 )

北工大matlab电子课件，陆续还有好多，很全的，希望大家下个痛快(err)