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[
Matlab]
gmm.rar
Creates a Gaussian mixture model with specified architecture.MIX = GMM(DIM, NCENTRES, COVARTYPE) takes the dimension of the space
DIM, the number of centres in the mixture model and the type of the
mixture model, and returns a data structure MIX.
Category:
matlab Upload User：
cdjinpeng Size：
2K
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[
Matlab]
kmeansNetlab.rar
... cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means
algorithm to set the centres of a cluster model. The matrix DATA
represents the data which is being clustered, with each row
corresponding to a vector. The sum of squares ...
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[
Matlab]
misc.rar
... samples from discrete distribution.
erfc2- Normal cumulative distribution function.
gmmsamp- Generates sample from Gaussian mixture model.
gsamp- Generates sample from Gaussian distribution.
cmeans- C-means (or K-means) clustering algorithm.
...
Category:
matlab Upload User：
yongqian Size：
21K
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[
Java/JSP]
TableSorterDemo.rar
TableSorterDemo is like TableDemo, except that it inserts a custom model-- a sorter-- between the table and its data model. It also has column tool tips.
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[
Matlab]
1.rar
Face Alignment Using an Improved Active Shape Model
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[
Matlab]
fuzzy.zip
... a fuzzy architecture, inspired to Takagi-Sugeno approach, on the basis of a training set of N (single) output-( multi) input samples.The returned model has the form1) if input1 is A11 and input 2 is A12 then output = f1 (input1, input2) 2) if input1 is ...
Category:
AI-NN-PR Upload User：
best_xf Size：
50K
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[
Matlab]
RAP.zip
Poisson model-based image retrieval and identification of the original: The Rate Adapting Poisson (RAP) model for Information Retrieval and Object Recognition
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[
WORD]
rj.rar
... has: ① waterfall model (waterfall model) ② Incremental models/evolution/iteration (incremental model) ③ the prototype model (prototype model) ④ spiral model (spiral model) ⑤ fountain models (fountain model ) ⑥ intelligent model (intelligent model) 7 ...
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[
Matlab]
MS_AR_FEX.zip
... folder contains instructions (and m files) for passing you own initial parameters to the fitting function.
I also included a simple simulation script that will create random initial coefficients
(under the proper bounds) and fit the model to the data.
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