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AM_costas_loop
在matlab中利用Costas环对AM通信系统进行载波相位跟踪,代码中带有详细注释。(Costas loop in matlab using communication systems on the AM carrier phase tracking, the code with detailed comments.)
- 2010-10-04 02:59:11下载
- 积分:1
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MOPSO
multiobjective pso algorithm that give fast and good answer for most optimization problem
- 2014-03-29 00:27:14下载
- 积分:1
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quadetest123
Quade test for non parametric two way ANalysis Of VAriance
- 2010-10-26 06:51:59下载
- 积分:1
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S-function-manual
S函数说明书,说明了S函数的模板样式,以及一些编写的注意事项(S-function manual, the S-function template styles, as well as a number of precautions written)
- 2013-03-11 10:33:59下载
- 积分:1
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fuuzy
程序是模糊MPPT控制,包括三个模块,光伏电池模块
模拟boost电路模块
(mppt MPPT control program is vague. Consists of three modules, photovoltaic module analog boost circuit module)
- 2021-04-08 21:59:00下载
- 积分:1
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gabor_11_15_01.tar
说明: 一个有关eigenface的matlab
例程(one of the Matlab routines eigenface)
- 2006-04-08 15:35:41下载
- 积分:1
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lms
这个程序关于语音信号的消噪,实现了一个基于最小均方误差算法的自适应噪声抵消器(This program about the speech signal de-noising, to achieve a minimum mean square error algorithm based on adaptive noise canceller)
- 2013-07-27 11:23:23下载
- 积分:1
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EasyKrig_V3
克里金法广泛地应用于地下水模拟、土壤制图等领域,是一种很有用的地质统计格网化方法。它首先考虑的是空间属性在空间位置上的变异分布.确定对一个待插点值有影响的距离范围,然后用此范围内的采样点来估计待插点的属性值。该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。它是考虑了信息样品的形状、大小及与待估计块段相互间的空间位置等几何特征以及品位的空间结构之后,为达到线性、无偏和最小估计方差的估计,而对每一个样品赋与一定的系数,最后 进行加权平均来估计块段品位的方法。(Kriging is a technique that provides the Best Linear Unbiased Estimator of the unknown fields (Journel and Huijbregts, 1978 Kitanidis, 1997). It is a local estimator that can provide the interpolation and extrapolation of the originally sparsely sampled data that are assumed to be reasonably characterized by the Intrinsic Statistical Model (ISM). An ISM does not require the quantity of interest to be stationary, i.e. its mean and standard deviation are independent of position, but rather that its covariance function depends on the separation of two data points)
- 2013-11-27 09:56:06下载
- 积分:1
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random_walk_3D
Brownian motion. A random walk is similar to markov process, however a
markov process has no memory, where a random walk uses an initial state.
The next step in the walk does not necessarily depend on your current
state but will be referenced from your current state, that is to say the
random vector is added to your current state. depending on complexity
- 2013-02-13 05:07:51下载
- 积分:1
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Desktop
基于LMS和RLS的自适应滤波器应用仿真(LMS adaptive filter simulation-based applications and RLS)
- 2013-11-26 13:19:43下载
- 积分:1