model

可以实现瑞利衰落的源代码，在幅度调制下实现(Rayleigh fading can be achieved the source code, in the amplitude modulation to achieve)

此代码产生一个16QAM信号，通过高斯白噪声信道后，对其使用常模盲均衡算法，最后输出星座图和收敛图。(This code generates a 16QAM signal, through the white Gaussian noise channel, the norm for its use of blind equalization algorithm, the final output constellation map and the convergence plan.)

掌纹识别的matlab程序，包括最大内切圆求法，KL变换，小波变换，欧式距离识别方法(Palmprint recognition matlab program, including the largest inscribed circle Method, KL transform, wavelet transform, Euclidean distance to identify methods)

LPI国外的雷达教程上的源程序，可以对照书上讲解进行学习(LPI tutorials on the radar of foreign source, can explain the book to learn the control)

基于MATLAB的，求解线性方程组的雅可比迭代法和高斯-赛德尔迭代法的比较 (Than the iteration method and Gauss- Seidel iterative method based on MATLAB, solving linear equations of Jacques)

双向RRT算法，可以生成随机地图，然后通过带对比择优的双向RRT算法完成路径规划.可以在matlab下正确运行(bidirectional RRT path planning based on comparison optimization )

确定信号和非确定信号的产生，各种滤波器的设计，对信号的频谱分析，滤波后信号的频谱分析等功能。有利于信号与系统、数字信号处理相关课程的学习与理解(Determine the signal and non-deterministic signal generation, a variety of filter design, spectral analysis of the signal, filtered signal spectrum analysis functions. Favorable signals and systems, digital signal processing related courses of study and understanding)

方波函数的傅里叶展开-自己编的小程序，希望能有所帮助(Square wave function )

用蒙特卡洛方法计算圆周率的程序,可以精确到第四位小数(a mento karlo method compiled in matlab)

摘要:提出了一种新型的人工免疫算法用来解决多目标函数优化问题。基于自然免疫系统固有的优良特性对算法进行了设计和分析。 最后,算法对3个较复杂的多目标问题进行了优化,优化结果能很好地覆盖问题的Pareto最优面,并且把算法与某些混合遗传算法进行 了对比实验,表明人工免疫算法在解决多目标优化问题上具有可观的研究前景。 (Abstract:In order to effectively solve multiobjective optimization problems, a novel artificial immune algorithm is proposed. It is de signed and analyzed based on excellent intrinsic features of nature immune systems. Additionally, the algorithm sensitivity to its tuning pa rameters is briefly assessed. Finally, the algorithm is applied to solve three complex multiobjective optimization problems and the results ca perfectly map the Pareto-optimal fronts. By comparing the algorithm with some genetic algorithms, it shows the good prospect to apply ar tificial immune system to solve multiobjective optimization problems. )