Virtual-modems

Matlab中没有现成的Lagrange插值函数，必须编写一个M文件实现Lagrange插值。 设n个节点数据以数组x0,y0 输入（注意Matlat的数组下标从1开始），m 个插值点以数组 x输入，输出数组y 为 m个插值。 编写一个名为lagrange.m的M文件。(Matlab is not off-the-shelf Lagrange interpolation function, we must realize the preparation of an M file Lagrange interpolation. N nodes based data to an array of x0, y0 input (Note Matlat subscript of the array starting at 1), m a x interpolation points to the array input and output array y for m months interpolation. Lagrange.m the preparation of a M-file.)

说明：  熟悉MATLAB信息统计分析的各种命令；会用MATLAB的信息统计分析的命令进行各种信息统计分析。(Familiar with a variety of statistical analysis of MATLAB command information will use the information MATLAB commands statistical analysis statistical analysis of all kinds of information.)

Ultrasound simulation(Ultrasound simulation FILD II)

无约束多维极值问题,适合数学计算,优化分析等极值问题的求解(Unconstrained multi-dimensional extremum problem, is suitable for mathematical calculations, the extremum problems of solving optimization analysis, etc )

这是一个基于空时分组编码的MIMO_OFDM通信系统的仿真设计。此系统包括QPSK调制解调解调，IFFT调制，空时编解码，基于训练符号的信道估计等通信模块。 (This is a space-time block coding based simulation design MIMO_OFDM communication systems. This system includes a QPSK modulation and demodulation demodulation, IFFT modulation, space-time coding and decoding, channel estimation based training symbol communication module.)

This function make iteration classification to find the best feature combination

OFDM系统的仿真程序，有详细的注释，方便学习，内容包括PSK调制，QAM调制等。(OFDM system simulation program, detailed notes, facilitate learning, including PSK modulation, QAM modulation.)

PSO基本实现过程的详细演示，适合初学者进一步加深对理论的理解，推荐使用(A detailed presentation of the basic PSO implementation process, suitable for beginners to further deepen the understanding of the theory, recommended the use of)

直方图压缩模板，输入的一定bins的直方图，输出48bins的直方图，可用于图像识别，在对图像提取直方图特征后进行降维操作(Compression template histogram, histogram bins certain input, output 48bins histogram, can be used for image recognition, the histogram of the image feature extraction operation after the dimension reduction)

主要是应用pso工具箱来优化函数griewank，实现粒子群对函数的测试(Mainly applications pso toolbox to optimize function griewank, and particle swarm function test)