modulat16qam

数学建模仿真maple的教程，很多人都用matlab进行科学研究，其实数值计算功能最强大的是maple，几个语句就能实现matlab很难实现的数学运算，这本书很经典，最总要的是Word版本，很方便移植到程序上验证的哦(Mathematical modeling and simulation maple tutorial, many people are using matlab for scientific research, in fact, the most powerful numerical calculation is maple, several statements can be very difficult to achieve matlab mathematical operations, this book is classic, the best always the Word version, it is easy to transplant procedure validation Oh)

希尔伯特黄变换中的第一步EMD的matlab代码，希望对大家有用。(Hilbert-Huang transform in MATLAB code for the first step of EMD, hope useful to everybody)

matlab上关于整数优化设计的一个很好源程序(matlab on integer optimization design a good source)

njust雷达原理教程，内容最全面，解压后为pdf版，值得一看！(njust Radar principle，The most comprehensive。)

stready heat conduction in a plate

本代码使用matlab工具实现了一幅图片的位面图提取，且实现了在某个位面上加密信息、恢复信息的功能。并给出三幅图片的运行结果展示。(This code uses the matlab tool to achieve a picture of the bit plane map extraction, and the realization of the encrypted information in a bit plane, the function recovery information. And gives the results of running three pictures show.)

numerical analysis of histogram

Matlab源码，主要采用时域有限差分(FDTD)法实现1D、2D的电磁仿真。(This directory contains MATLAB files for 1D simulations of electromagnetic fields. Included are wave propagation in free space, in dissipative media (sigma nonzero), and in dispersive media (debye medium).)

Fourie Crypt. Encrypt and decrypt programs

说明：  遗传算法（Genetic Algorithm，GA）最早是由美国的 John holland于20世纪70年代提出,该算法是根据大自然中生物体进化规律而设计提出的。是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。该算法通过数学的方式,利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。(Genetic algorithm (GA) was first proposed by John Holland of the United States in the 1970s. It is designed and proposed according to the evolution law of organisms in nature. It is a computational model of biological evolution process simulating natural selection and genetic mechanism of Darwin's biological evolution theory. It is a method to search the optimal solution by simulating natural evolution process. The algorithm transforms the solving process of the problem into a process similar to the crossover and mutation of chromosome genes in biological evolution by means of mathematical method and computer simulation. When solving complex combinatorial optimization problems, compared with some conventional optimization algorithms, it usually can get better optimization results quickly. Genetic algorithm has been widely used in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life.)