turbo_decoder1

RS 码译码源程序,在Visual c++下可对比4元域上的RS码进行纠错译码.(RS decoder source, in Visual c contrast under four yuan domain of RS error correction code for decoding.)

对美国由次贷危机引起的金融风暴进行了研究，分别建立了次贷危机产生机理的模型和金融风暴的判定模型，并用计算机对模型进行了仿真。通过仿真分析得出了利率和房价的变动是形成次贷危机的直接原因，而信心指数却是形成危机的根本原因的结论。况，实现城市平面十字路口的微观仿真，通过仿真得到信号灯的最佳控制方式与这一控制方式下的交通拥堵情况。然后在取消左转的条件下从路网的角度分析道路交通流，通过对路网模型的分析，针对其较大的复杂度和边界缺陷，我们建立了其等效模型。改变进入系统的车流的性质仍然在单个十字路口建立模型进行仿真。经过两个模型的对比，我们得出“取消左转”这一方式有利于改善道路交通拥堵问题。最后提出其他可行的“无左转”交通流组织形式，并进行简单分析。(Subprime mortgage crisis matlab simulation)

this code is one of our homework in image processing which belong to gonzales

处理信号的时频分析，脉冲响应的相关分析算法并检验，一种噪声辅助数据分析方法。( When processing a signal frequency analysis, Related impulse response analysis algorithm and inspection, A noise auxiliary data analysis method.)

含有PUMA560（机械臂）的MATLAB仿真教程以及官方的Robotic Toolbox教程(MATLAB simulation tutorials containing PUMA560 (robotic arm) and official Robotic Toolbox tutorial)

说明：  李氏指数的一些程序，希望对大家有用，啊哈哈和！(Lipschitz exponent of some of the procedures, we hope to be useful, ah ha ha and!)

S-Function（系统函数）为扩展Simulink® 的性能提供了一个有力的工具。以下下节阐述了什么是 S-Function，为什么可以使用S-Function，以及怎样编写自己的S-Function。(S-Function (system function) for the expansion of the performance of Simulink ® provides a powerful tool. The following section describes what is under the S-Function, Why you can use the S-Function, and how to write your own S-Function.)

模拟2个独立窄带信号分别以20°，60°的方向入射到均匀线阵上，信号间互不相关，与噪声相互独立，噪声为理想高斯白噪声，阵元间距为入射信号波长的1／2，信噪比为20dB，阵元数为10，采样快拍次数为200。(Simulate two independent narrowband signals in the direction of 20 °, 60 ° of the incident on the ULA, among signal unrelated, independent noise, the noise is ideal Gaussian white noise, the array element spacing of the incident signal wavelength of 1/2, the signal to noise ratio is 20dB, the array element number 10, the sampling frequency of 200 snapshots.)

用于分类的主判别变量算法(principal discriminant variate algorithm) ( principal discriminant variate algorithm for two classes, x1 and x2. x1 is the training samples in the 1st class with each column being the spectrum characterizing the corresponding sample. x2 is the training samples in the 2nd class with each column being the spectrum characterizing the corresponding sample. lamda is the penalty weight defining the balance between FLDA and PCA. dvnum is the number of principal discriminant variates to be computed. A defaul value for dvnum is 2. dv is the principal discriminant variates. scores is the matrix with each row being the scores of the samples on the corresponding principal discriminant variate. xmean is the mean spectra of the sample, which was used for mean-centering the data in training and prediction. )

matlab 源文件，核构建算法，经典算法(matlab source files, nuclear build algorithm, the classic algorithm)