xianxingzhengshuguihua

this paper has different new technology of algorithm to be used in wireless communication

一种对连续野值不敏感的鲁棒卡尔曼滤波器， 对清华学报上的一篇文章的仿真，能有效剔除连续型野值 (A field value is not sensitive to the continuous robust Kalman filter, for an article on the Tsinghua University policy, can effectively eliminate the value of continuous field)

matlab 传统板的FEM程序静力分析、模态计算(Analysis, modal calculation program FEM of traditional static matlab plate)

lof function over gray level transformation image

C/C++ and Matlab types convertor

说明：   该程序是使用Matlab仿真协同通信的DF（解码转发）基本性能，也可以作为学习Matlab 通信仿真的入门实例。 (This program is to simulate basic performance of collaborative communication DF (decoding forwarding)by using Matlab, also can be used as a learning Matlab communication simulation of introductory examples.)

利用全通滤波器的原理对于因信号进行改变相位，嵌入数字水印(use of the all-pass filter principle as a result of changes in signal phase, embedded digital watermarking)

这是一个基于MATLAB编写的BUTTERWORTH滤波器的程序.其中从s域到z域的变换是自己编写的,代替了MATLAB中的系统BUTTERWORTH的系统函数(对于毕业设计的学生,比较有用!!)(based on MATLAB BUTTERWORTH prepared by the filter process. From which z's domain to the domain transform their own preparation, instead of MATLAB system BUTTERWORTH system function (for graduate design students more useful! !))

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. 氀椀渀最樀椀愀渀.m Part initial value, using the Monte Carlo method to calculate the total cost. The preparation of their own normal distribution random number generator to generate normally distributed random numbers. lingjian.m is the first practice of the Monte Carlo method. accyouhua calibration value the function lingjian not a function, which gives the value of a set of calibration values. Annealing to determine the calibrated value/unitanneal ()---- Simulated Annealing 吀栀攀 continuous multiple variables combinatorial optimization problems 吀栀椀猀 is an exercise of the simulated annealing method, the results show that the simulated annealing is an effective method. 圀栀攀渀 the parameter selection is better (generally accompanied by a longer running time), simulated annealing results, however using MATLAB FMIMCON () generally achieve higher accuracy.)

说明：  Matlab demonstration script for frequency modulation