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GSA
Scrip to calculate the flow of potency with Gauss Seidel s method
Accelerated
- 2013-03-22 01:30:00下载
- 积分：1
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0.2-alpha
documentclass{beamer}
usepackage[frenchb]{babel}
usepackage[T1]{fontenc}
usepackage[latin1]{inputenc}
usetheme{Warsaw}
egin{document}
egin{frame}
Voici votre première page de présentation en LaTeX !
end{frame}
end{document}
- 2012-09-16 20:26:51下载
- 积分：1
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FDE熵
说明： 计算信号复杂度，复杂度高，继续分解，用在信号分解中(Computational complexity)
- 2021-03-12 16:26:31下载
- 积分：1
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ui_check_params
说明： 关于OFDM的CHECK部分程序,是用MATLAB做的(on OFDM CHECK part of the process is done using MATLAB)
- 2005-11-30 13:32:19下载
- 积分：1
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emd
经验模态分解法程序emd，运行准确，适合进行hilbert-huang变换的人员使用(a precess of emd)
- 2011-06-24 20:48:09下载
- 积分：1
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w3_generalization
machine learning 方面有关于Generalization and Bayesian Introduction的资料，语言是python(machine learning aspects of information concerning Generalization and Bayesian Introduction, language is python)
- 2013-12-07 23:11:31下载
- 积分：1
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PhaseAdjustment
用于分析行走中的人体目标的微动回波分析，改程序为微动分析中的相位调整m函数，可以被移植到其他相应代码中。(Fretting echo for the analysis of human walking target analysis, change procedures for the analysis of micro-m phase adjustment function, it can be ported to other appropriate code.)
- 2021-04-09 16:09:00下载
- 积分：1
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rgb2bayer
以全彩图像为输入，根据bayer cfa输出raw图像。附有操作例图。(With full color images as input, output based on raw bayer cfa image. With the operation of FIG.)
- 2015-04-14 17:05:20下载
- 积分：1
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QPSK
This source code give the explanation about generate QPSK simulation
- 2010-07-02 02:30:21下载
- 积分：1
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hsmm
隐马尔科夫模型是关于时序的概率模型，描述由一个隐藏的马尔科夫链随机生成不可观测的状态随机序列，再由各个状态生成一个观测而产生观测序列的过程。隐藏的马尔科夫链随机生成的状态的序列，称为状态序列；每个状态生成一个观测，而由此产生的观测的随机序列，称为观测序列。马尔科夫链由初始概率分布、状态转移概率分布以及观测概率分布确定(The hidden Markov model is a probabilistic model for time series. It describes the process of randomly generating unobservable state random sequences from a hidden Markov chain, and then generating an observation by each state to produce an observation sequence. A sequence of randomly generated states of hidden Markov chains, called a sequence of states; each state produces an observation, and the resulting random sequence of observations is called an observation sequence. Markov chain is determined by initial probability distribution, state transition probability distribution and observation probability distribution)
- 2019-05-27 12:01:38下载
- 积分：1
