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cauchy_2
工程最优化 共轭梯度法求解wood函数~！！！！(cauchy)
- 2009-11-21 11:14:33下载
- 积分：1
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particle-filter-for-tracking
A simple example showing how to track an object with particle filter. Likelihood is based on Bhattacharya distance of color histogram.
- 2010-02-20 03:48:59下载
- 积分：1
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matlab 代码
这是一份完善的管壳式气-气换热器设计型计算代码示例。(This is a Heat Exchanger Designer Matlab Code Sample for Chemical Engineering Design Area.)
- 2019-03-11 00:54:38下载
- 积分：1
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texture_code_and_thesis
4个收集的vc，matlab纹理检测，纹理分割代码和数篇IEEE纹理分割，纹理缺陷检测论文(Number of Posts IEEE texture segmentation, texture defect detection papers and four personal collection vc, matlab code texture segmentation)
- 2010-07-01 16:20:53下载
- 积分：1
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算法
马尔科夫蒙特卡洛算法的MATLAB应用示例(code for MCMC in MATLAB)
- 2020-10-12 23:07:32下载
- 积分：1
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MUSIC
MUSIC算法源程序MUSIC算法源程序MUSIC算法源程序MUSIC算法源程序MUSIC算法源程序(MUSIC algorithm source codeMUSIC algorithm source codeMUSIC algorithm source codeMUSIC algorithm source code)
- 2014-01-12 21:08:47下载
- 积分：1
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对于小位移和桥梁变形的测量
说明： 对于小位移和桥梁变形的测量，一种很好的算法，对研究匹配也具有参考价值(For the measurement of small displacement and bridge deformation, a very good algorithm, also has reference value for research matching)
- 2020-06-23 02:40:01下载
- 积分：1
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Matlab
Handbook of Practical MATLAB® for Engineers
Practical MATLAB® Basics for Engineers
Practical MATLAB® Applications for Engineers
- 2010-06-09 00:11:14下载
- 积分：1
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GMM-GMR-v1.2
GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Expectation-Maximization (EM) iterative learning algorithms. By using this model, Gaussian Mixture Regression (GMR) can then be used to retrieve partial output data by specifying the desired inputs. It then acts as a generalization process that computes conditional probability with respect to partially observed data.
- 2009-12-02 11:32:00下载
- 积分：1
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LHS
拉丁超立方抽样，调用方式如下：S=lhs(m,dist,mu,sigma,lowb,upb)
m: a scalar,the number of sample points
dist: A row with distribution type flags of basic random variables the
value of the flag can be 1 (for uniform distribution, 2(for normal distribution), 3(for lognormal)
and 4(for extreme type 1).
mu: A row vector comprising the mean value of basic random variables.
sigma: A row vector with its length equaligng to mu,including the standard
deviation of basic random variables.
lowb: a row vector with its elements are the lower bound of the sampling
interval
upb:a row vector with its elements are the upper bounds of the sampling
interval
dist,mu,sigma,lowb,upb must have the same length.
Output argument
S: sampling point matrix, of which each row is a sampling point.(code of Latin Hypercube Sampling)
- 2021-03-03 16:29:33下载
- 积分：1
