code-for-homework

关于求解线性规划单纯形法的matlab程序 (Simplex method of linear programming in matlab program)

二维曲线拟合方面的matlab工具箱代码，很实用(In two-dimensional curve fitting toolbox of matlab code, very useful)

VC和matlab平台编程，实现实时录音，与语音信号的断点检测。注意，不是查询方式，是回调函数实时处理。(VC and matlab platform for programming, real-time recording, and voice signals breakpoint detection. Note that the query is not a way, is a callback function, real-time processing.)

matlab仿真控制仿真时间的程序段,简单方便的在matlab界面控制仿真停止时间。(matlab simulation control simulation time block, simple and convenient interface control in matlab simulation stop time.)

matlab仿真，对卡尔曼滤波器的性能分析，包括均方误差等(matlab simulation, the performance of the Kalman filter analysis, including mean square error, etc.)

数据分析，其中包含了数据分析的基本源代码，是M文件的形式，并且还有PPT的相关教程(Data analysis, data analysis, which includes the basic source code, the M form of the document, and there' s tutorials PPT)

说明：  8. 单径瑞利信道中的四发四收V-BLAST： (1) 请设计一种具体的导引辅助的信道估计方法，用Simulink进行仿真，测量16QAM调制时的误码率性能。画出比特信噪比与信道估计均方误差的关系曲线，画出比特信噪比与误码率的关系曲线。 (4 Explain the working principle of convolutional encoding and decoding. Please use the Simulink simulation convolutional coding and Viterbi decoding method used to decode, in which the encoding, decoding all 8 single-path Rayleigh channel of the four rounds of four closed V-BLAST: (1) Please design a specific The guide-assisted channel estimation method, using Simulink for simulation, measurement 16QAM modulation bit error rate performance. Draw-bit signal to noise ratio and channel estimation mean square error curve, draw-bit signal to noise ratio and bit error rate curve.)

A test script indicating how to find the appropriate frequency spectrum of a time dependant signal using Matlab. An associated function is also included.

关于Matlab中常微分方程的数值解法以及其Matlab实验的源代码(Numerical solution of differential equations)

多天线的角辐射功率演示,包括2种天线阵,1为线性真,一为任意布置.(A MATLAB GUI platform for displaying the radiation pattern of a narrowband beamformer with user-defined array geometry. User can specify the array geometry, directions of incoming signals, noise level, and the types of beamformer by mouse clicks. Useful for gaining insight about collaborative beamforming in sensor networks and random arrays. )