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Exact(34)
Y i is the output target value for the ith training vector.
And five kinds of entropy are extracted as the training vector.
In addition, it leads to the best representation for each training vector.
Step 2. Apply the new training vector (x^{left( t right) }=left( {x_1, x_2, ldots,x_k } right) ).
In other words, the features of training vector (x_l^{(i)}) are compressed and represented in terms of these learned features.
A strategy of reinforced learning (RL) is proposed which exploits the advantages offered by fuzzy clustering algorithms, competitive learning and knowledge of training vector and codevector configurations.
Similar(26)
n is the number of training vectors.
Real time engine diagnostics-prognostics. Relevance training vectors.
The training vectors are centered and normalized according to (9).
The training vectors are generated according to (32).
Figure 10 shows the convergence of training trend with such an input training vectors.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com