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manual_thresh
mnualy threholding the image by using this code
- 2010-09-26 16:52:32下载
- 积分：1
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cluster-analysisprinciples
说明： 多元线性分析，之聚类分析原理资料2（与1不同）(Multiple linear analysis, the principle of cluster analysis data 2)
- 2011-04-07 11:13:12下载
- 积分：1
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matlab-gentic-algorithm
matlab genetic algorithm
- 2014-10-23 23:17:21下载
- 积分：1
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klm
利用Kalman滤波器通过测量信号估计x(n)的波形(Using Kalman filter estimates by measuring the signal x (n) waveform)
- 2011-01-04 22:42:08下载
- 积分：1
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pushang
实现低信噪比下的语音断电检测，谱熵端点检测，优于双门限端点检测法(Low-power voice SNR detection, spectral entropy endpoint detection, better than the two-endpoint detection threshold)
- 2011-11-14 11:10:19下载
- 积分：1
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servo_control_torobot
this program can control the servo motor by servo controller board torobot 24 servos
- 2013-11-18 19:02:26下载
- 积分：1
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adaptdemos
自适应滤波器 采用改进的rls算法 LMS 算法 (adaptive filter optimal rls and lms algorithms)
- 2021-01-25 20:38:42下载
- 积分：1
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lms_rls
用于自适应LMS滤波器的设计以及自适应RLS滤波器的设计(LMS adaptive filter for the design of RLS Adaptive Filter Design)
- 2020-11-21 17:19:35下载
- 积分：1
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MCMCcourse-BOOK
此为一篇介绍mcmc方法的外文文献 非常适合刚刚接触mcmc方法的初学者(This paper introduces the readers of the Proceedings
to an important class of computer based simulation
techniques known as Markov chain Monte Carlo
(MCMC) methods. General properties characterizing
these methods will be discussed, but the main emphasis
will be placed on one MCMC method known as the
Gibbs sampler. The Gibbs sampler permits one to simulate
realizations from complicated stochastic models in
high dimensions by making use of the model’s associated
full conditional distributions, which will generally have
a much simpler and more manageable form. In its most
extreme version, the Gibbs sampler reduces the analysis
of a complicated multivariate stochastic model to the
consideration of that model’s associated univariate full
conditional distributions.)
- 2013-11-13 10:33:29下载
- 积分：1
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path_short
求无向无权值复杂网络的各点对之间的最短路径，以及网络平均路径长度(abtain the shortest path of a complex net and get the averange path of the whole net)
- 2012-03-11 10:35:41下载
- 积分：1
