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RSSI
基于RSSI的定位，已知发射节点的发射信号强度, 接收节点根据接收信号的强度, 计算出传播损耗, 利用理论的或经验的信号传播模型将传播损耗转化为距离, 然后再计算出节点的位置(RSSI-based positioning, known to launch the node transmission signal strength, the receiving node according to received signal strength, transmission loss calculated using the theory or experience loss of signal propagation model will spread into the distance and then calculate the location of the node)
- 2021-02-23 17:39:40下载
- 积分：1
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ACO-PSO
蚁群算法（ACO）和粒子群算法（PSO）的混合算法解决旅行商问题（TSP）的matlab代码(Ant colony optimization (ACO) and particle swarm optimization (PSO) of the hybrid algorithm to solve traveling salesman problem (TSP) in matlab code)
- 2021-04-13 14:58:56下载
- 积分：1
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capon_new
beamforming, capon, 和music 三种波达方向定位算法的matlab仿真源代码(beamforming, capon, and the music of three of the direction of arrival location algorithm matlab simulation source code)
- 2009-04-01 11:13:39下载
- 积分：1
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VC_MATLAB7SharedLibrary
调用MATLAB7 Compiler 产生共享库程序的方法介绍，有如下的大致结构：
1．声明变量或者是函数作为输入变量；
2． 调用 mclInitalizeApplication函数，并测试是否成功，该函数设置了一个全局的MCR
状态，并且构建MCR实例；
3． 对于每个库，调用一次<libraryname>Initalize函数，为库创建一个MCR 实例；
4． 调用库中的函数，并处理其结果（这是程序的主要部分）；
5． 为每个库调用一次<libraryname>Terminate函数，用于注销相联系的MCR；
6． 调用 mclTerminateApplication函数，释放与全局MCR状态相联系的资源；
7． 清除变换，关闭文件等，然后退出。(VC+ MATLAB7 C Shared Library Target)
- 2009-06-06 10:46:54下载
- 积分：1
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AF
说明： Amplify and Forward matlab code
- 2013-12-13 07:27:37下载
- 积分：1
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PCA
实现图像的降维处理,可以缩短大量的计算时间。(Dimensionality reduction of image processing, a lot of computation time can be shortened.)
- 2013-11-19 21:17:01下载
- 积分：1
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Program-to-plot-the-BER-of-OFDM-in-Frequency-sele
Program to plot the BER of OFDM in Frequency selective channel
- 2014-02-19 22:07:54下载
- 积分：1
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gaussfir
实现短波信道中瑞利衰落和多普勒扩展的代码，比较使用(Achieve short-wave Rayleigh fading channels and the expansion of the code Doppler to compare the use of)
- 2009-04-01 19:29:58下载
- 积分：1
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Untitled
用matlab仿真模糊控制器，有一定的帮助(fuzzy pid controller)
- 2009-05-08 12:40:50下载
- 积分：1
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fit_ML_rayleigh
fit_ML_rayleigh - Maximum Likelihood fit of the rayleigh distribution of i.i.d. samples!.
Given the samples of a rayleigh distribution, the PDF parameter is found
fits data to the probability of the form:
p(r)=r*exp(-r^2/(2*s))/s
with parameter: s
format: result = fit_ML_rayleigh( x,hAx )
input: x - vector, samples with rayleigh distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
s - fitted parameter
CRB - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type- ML
- 2011-02-09 19:10:54下载
- 积分：1
