exm1001_1

中文教程。本教程提供了使用MATLAB的实践性指导，它基于MATLAB6.0版，内容由浅入深，特别是本书对每一条命令的使用格式都作了详细而又简单明了的说明，并配备了例题加以说明其用法，因此，对于初学者自学是很有帮助的；同时，又对数学中的一些深入问题如数值分析、稀疏矩阵、优化理论以及模糊数学等问题进行了较为详细的论述，因此，该书也可作为科技工作者的科学计算工具书。(Chinese tutorial. The Guide provides practical guidance to the use of MATLAB, which is based on MATLAB6.0 edition, the content of easy-to-digest, especially the book on the use of each command formats are explained in detail and simple description and sample questions to be equipped with its usage, therefore, self-study is very helpful for beginners At the same time, some of mathematics in depth issues such as numerical analysis, sparse matrix, optimization theory and fuzzy mathematics, etc. more detail, therefore, the book can also be used as science and technology workers in scientific computing tool.)

说明：  该程序涉实现目标检测功能，IIR滤波器的背景估计法的背景相减目标检测 && canny(this is a goal detection program, a IIR filter )

it is an ebook for learning pid controller design with matlab functions

本代码主要仿真了维特比解码（5,4,2）的SPC码的仿真使用以及其性能(This code simulated Viterbi decoding (5,4,2) SPC code simulation use, as well as its performance)

Application Architecture Guide v2，NET架构设计的参考书籍(Application Architecture Guide v2, NET architecture design reference books)

source code for imageproccesin

Scientific and Engineering C++. Book for developing applications in C++

该函数计算单元的刚度矩阵，输入弹性模量E、横截面的惯性矩I和梁单元的长度L，输出单元的刚度矩阵(Computational unit stiffness matrix)

说明：  基于MatlabWeb服务器的虚拟实验平台的实现(MatlabWeb server based implementation of the virtual experiment platform)

Wavelet denoising For using this code need to use signal toolbox and general toolbox in your matlab In the first part of this assignment, we asked to obtain a (black-and-white) digital image of size 512 by 512 and then generate noisy image by adding a Gaussian noise but under the condition of having SNR=20dB by select the suitable value of variance for Gaussian noise formula. Second step is performing wavelet denoising using the hard thresholding (Use the db 6 for four levels) in the condition of finding the optimal thresholding value of T in terms of the SNR obtained. It means that, we should find the highest SNR value by finding the suitable value for threshold. Then we asked to do the same process but this time using soft thresholding. Finally for the last part of question one, we should compare the results of the obtained SNR with the recommendations of 3*sigma for the hard thresholding and 3/2*sigma for the soft thresholding.