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butterworth
MATLAB环境下实现butterworth 低通滤波器仿真(MATLAB butterworth )
- 2010-05-27 11:07:45下载
- 积分:1
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CoverageCalculation
wireless coverage calculation source code for matlab
- 2011-07-18 21:31:27下载
- 积分:1
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mfcc
mfcc特征提取的程序,程序还需要enframe和melbankm,会一起上传(mfcc feature extraction procedures, the program also needs enframe and melbankm, upload them together)
- 2013-08-22 16:59:01下载
- 积分:1
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FeatureExtract
matlab code for feature extraction
- 2013-03-06 13:33:03下载
- 积分:1
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2DPCA
自己写的一个2DPCA的代码,可使用,可调节,有适当的地方可改动(2DPCA。。written by myself maybe useful for you,please to know it)
- 2011-10-21 15:39:17下载
- 积分:1
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MATLAB7.0vc++andmatlabprogram
《精通matlab7.0混合编程》的例子程序,其中涉及MATLAB程序和VC++程序,其中大部分为改书所附光盘。()
- 2007-08-12 19:15:56下载
- 积分:1
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emd
说明: matlab开发环境,emd源代码程序,提供大家学习交流(matlab development environment, emd the source code program, to provide them to learn from the exchange)
- 2010-05-03 18:55:14下载
- 积分:1
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kalman_falling
This program helps in kalamn filter falling body simlation with EKF
- 2010-05-10 18:01:52下载
- 积分:1
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MLNB
朴素贝叶斯分类器,朴素贝叶斯分类器朴素贝叶斯分类器(Naï ve Bayes Classification,Naï ve Bayes Classification,Naï ve Bayes Classification)
- 2020-12-07 20:29:21下载
- 积分:1
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SPGP_dist
这是一个关于稀疏高斯过程的matlab源码,可以用于计算测试输入的高斯预测值。( spgp_pred computes the SPGP predictive distribution for a set of
test inputs. You need to supply a set of pseudo-inputs or basis
vectors for the approximation, and suitable hyperparameters for the
covariance. You can use any method you like for finding the
pseudo-inputs , with the simplest obviously being a random subset of
the data. It is coded for Gaussian covariance function, but you could
very easily alter this. It is also fine to use for high dimensional
data sets.
spgp_lik is the SPGP (negative) marginal likelihood and gradients
with respect to pseudo-inputs and hyperparameters. So you can use this
if you wish to try to optimize the positioning of pseudo-inputs and
find good hyperparameters, before using spgp_pred . I would recommend
initializing the pseudo-inputs on a random subset of the data, and
initializing the hyperparameters sensibly. Its current limitations are
that 1) it is slow and memory intensive for high dimensional data sets
2) it is heavi)
- 2021-05-13 07:30:02下载
- 积分:1