HW1

UMTS FDD Downlink Simulink Model Simulates UMTS Physical layer FDD for Downlink.

这个程序是用SLM算法抑制峰均功率比的matlab仿真程序，对100000个OFDM符号进行统计然后表征算法对PAPR的改进程度，绝对可以运行(this process is inhibited by SLM algorithm PAPR of Matlab simulation program, to 100,000 OFDM symbols statistical algorithm then characterization of the degree of the improvement PAPR, absolutely can run)

一种改进的果蝇算法，文件中包含matlab实现代码和算法说明(an improved FOA, in the file, the demo develped by MATLAB and the produre of lgms-foa is obtained)

说明：  用matlab实现音频信号在频率上的处理( Programs with matlab realizes the tonic train signaling equalization treatment )

matlab code for simulation SNR to verify capcity of channel

Laplacian Pyramid: 用MATLAB实现并改进的图像拉普拉斯金字塔分解以及隐藏信息嵌入的源码。程序展示了Laplacian Pyramid Decomposition 在图像嵌入隐藏信息的重要作用。(Laplacian Pyramid: Based on MATLAB, original codes realize the improved Laplacian Pyramid Decomposition and the method to embed hidden information into images.Codes show its significance in embedding hidden info into images.)

说明：  三目标微电网优化调度，减少成本，提升效益(Optimal Dispatching of Microgrid)

this is a file about c++ in matlab.i hope that will been saisfied.

Active contour with level set and Kass methods. start with initial circles around objects and then converge in edges of objects, matlab

lingjian.m-----蒙特卡罗方法 lingjian.m使用零件初始值，用蒙特卡罗方法算出总费用。其中使用了自己编制的正态分布随机数发生器产生正态分布随机数。lingjian.m是对蒙特卡罗方法的一次练习。 accyouhua为标定值的函数，而lingjian不是一个函数，在其中已给出了一组标定值的值。 退火确定标定值/unitanneal()----模拟退火 连续型多个变量组合优化问题 这是对模拟退火方法的一次练习，结果证明模拟退火确实是一个行之有效的方法。 当参数选择较好时（一般也伴随着运行时间的加长），模拟退火的结果较好，然而用MATLAB的FMIMCON()一般可达到更高的精度。(lingjian.m----- Monte Carlo method lingjian.m part the initial value, using the Monte Carlo method to calculate the total cost. The use of the preparation of their own normal distribution random number generator to produce a normal distribution of random numbers. lingjian.m yes to the first practice of the Monte Carlo method. accyouhua calibration function, and lingjian is not a function, which has given the value of a set of calibration values​ ​ . Annealing to determine the calibration value/unitanneal ()---- Simulated Annealing Combinatorial optimization problem of continuous multiple variables This is a practice of simulated annealing method, the results show that simulated annealing is an effective method. Parameter selection is better (usually accompanied by longer running time) the results of simulated annealing, however the MATLAB FMIMCON () generally achieve higher accuracy. )