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The vector size is 256 bits.
The greater the vector size, the more processing is required.
Flux and membrane capacity decreased significantly with increasing vector size (6 72 kb).
Here, we need to determine another parameter that controls the input vector size, namely, context-size.
The coefficients vector size is defined as with ℓ = 1,2.
This restricts the parameter vector size to the available memory on only one node.
When more blocks are involved, the final feature vector size becomes many times the original one.
Thirdly, extract local binary patterns (LBP) of detected regions having feature vector size (1 × 59).
The order of assembly affected vector size, surface charge, stability, and ability to bind and release DNA.
For this reason, many linear and nonlinear methods for vector size reduction are applied (PCA, LDA, ICA,...).
As it reduces vector size from m to (log_2(m)) we choose to call it log-m embedding.
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