Geographical-Modification

OFDM的实现过程及其解调过程的仿真分析。(The implementation of OFDM demodulation process simulation and analysis.)

Run Application =============== Windows: Doubleclick the BicAT_v2.2.jar file Linux: type ./run_linux to start the application. Solaris: type ./run_solaris to start the application. possible problems: ================== Make sure the environment variables are properly set! CLASSPATH (should be ok) LD_LIBRARY_PATH = ./lib/linux ./lib/solaris Sample Data Files ================= dataSample_1.txt - use offsets (1,1) (data are already logarithmized) dataSample_2.txt - use offsets (1,1) (Run Application =============== Windows: Doubleclick the BicAT_v2.2.jar file Linux: type ./run_linux to start the application. Solaris: type ./run_solaris to start the application. possible problems: ================== Make sure the environment variables are properly set! CLASSPATH (should be ok) LD_LIBRARY_PATH = ./lib/linux ./lib/solaris Sample Data Files ================= dataSample_1.txt- use offsets (1,1) (data are already logarithmized) dataSample_2.txt- use offsets (1,1) )

说明：  复化simpson公式求二重积分的matlab程序，对于无振荡函数的二重积分效果很好！(Minute of Double Integral formula for the Matlab procedures, without oscillation function for the Double Integral good results!)

this is source seperation matlab code

本程序可以显示常见激光模式分布图，如TE00，TE01,TE10,TE22等，有助于对激光横模的理解！(This program is to help students to understand to the laser mode )

说明：  采用平面波展开法计算2维光子晶体的能带图(The plane wave expansion method two-dimensional photonic crystals with map)

说明：  倒立摆模糊控制程序，基于matlab编写，用于模糊控制仿真(inverted pendulum control procedures, based on Matlab prepared for Fuzzy Control Simulation)

Henon吸引子是混沌和分形的著名例子,迭代模型为xk+1=1+ax2k+byk,yk+1= xk.最常见的参数取值为a=1.4,b=0.3 .(The Henon attractor is chaotic and fractal famous example of the iterative model xk+1 = 1+ ax2k+ byk yk+1 = xk. The most common parameter values ​ ​ a = 1.4, b = 0.3)

数字基带系统的传输.比较了PSK，ASK，FSK系统的误码率(Digital baseband transmission. Compared PSK, ASK, FSK system bit error rate)

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)