scaleif

基于OFDM的无线宽带系统仿真It contains mainly two parts, i.e. link-level simulator and system-level simulator. Link-level simulator focus on a single-cell single-user scenario, where signal is transmitted from tx, and estimated at rx. Comparing the difference in tx/rx signal, the error rate can be found out. The output of the link-level simulator is the BLER/BER vs. SNR mapping table, that can be used for the system-level simulation. System-level simulator focus on a multi-cell multi-user scenario. For the sake of simplicity, it takes the mapping table aquired in the link-level simulation, measure the actural SNR, and finds the corresponding error rate.(OFDM-based wireless broadband system simulation It contains mainly two parts, ie link-level simulator and system-level simulator.Link-level simulator focus on a single-cell single-user scenario, where signal is transmitted from tx, and estimated at rx . Comparing the difference in tx/rx signal, the error rate can be found out. The output of the link-level simulator is the BLER/BER vs. SNR mapping table, that can be used for the system-level simulation.System- level simulator focus on a multi-cell multi-user scenario. For the sake of simplicity, it takes the mapping table aquired in the link-level simulation, measure the actural SNR, and finds the corresponding error rate.)

code for Ferrigno&D Amico window

自己编的，使用Root_Music算法对3个复正弦加白噪声的随机过程的频率进行估计，并附有仿真图片(Own series, Root_Music algorithm to estimate the three complex sinusoidal frequency of the random process of white noise with simulation pictures)

Wilson法求解动力方程，可以画出节点的位移响应(Wilson method for solving dynamic equations, you can draw the node displacement response)

Grefenstette编码法的MATLAB实现 本文在MATLAB环境下编程实现针对TSP问题的Grefenstette编码法,并将其同基本遗传算法相结合,仿真求解一个 15点的TSP问题(Grefenstette coding method to achieve this paper, the MATLAB environment in MATLAB programming for the TSP problem Grefenstette coding method and genetic algorithm with the basic combination of a 15-point simulation of the TSP problem)

Histogram equalization...Image processing

简单的遗传算法解决优化问题的汇编代码，包括单变量无约束优化、单变量有约束优化及多变量优化问题，并配以实例进行说明(Genetic Algorithms)

逐步判别分析的主函数 用于分类 [sel,c,c0,re,P]=StepclaassV2(data,[50 50 50],data,10) 输入变量 x为训练集.每行为一个样本，每列为一个变量. Class_x,为训练集的分类情况，一行，为各类样本数量,例如[5 6 9] Test为待分类样本. 输出变量：sel为选择的变量序号，c,c0为拟合出的判别函数.re为对Test的判别结果,P为其后验概率. author 王新 2012.4.8 例子Sample: load fisheriris x=meas Class_x=[50,50,50] Test=meas(1:5,:) Fa1=4 [sel,c,c0,re,P]=StepclaassV2(x,Class_x,Test,Fa1)( Stepwise discriminant analysis for the classification of the main function [sel, c, c0, re, P] = StepclaassV2 (data, [50 50 50], data, 10) input variables x as the training set, each conduct a sample of each as a variable. Class_x, the classification for the training set, a row, the number of samples for all types, for example, [5 6 9] Test sample to be classified. output variable: sel for the selected variables serial number, c, c0 is fitted discriminant function. re discrimination results for the Test, P its posterior probability. author Wang 2012.4.8 examples Sample: load fisheriris x = meas Class_x = [50,50,50] Test = meas (1:5, :) Fa1 = 4 [sel, c, c0, re, P] = StepclaassV2 (x, Class_x, Test, Fa1))

自己编写的特征系统实现算法程序，可以用作参考，希望对大家有所帮助(I have written algorithm program system features, can be used as a reference, we hope to help)

实现EMD分解，并对原始信号进行hilbert谱分析，通俗易懂，操作方便(The realization of EMD decomposition, and the original signal hilbert spectral analysis, user-friendly, easy to operate)