sparse code造句

This is why sparse coding became an alternative to grandmother cells.
The sparse coding for the input then consists of those representative patterns.
Sparse coding may be a general strategy of neural systems to augment memory capacity.
They are the properties of sparse coding instead.
Given a potentially large set of input patterns, sparse coding algorithms ( e . g.
It's difficult to find sparse code in a sentence. 用sparse code造句挺难的

Sparse coding starts with the activation of moderately small sets of neurons in a small region of the brain.
The capacity of sparse codes may be increased by simultaneous use of temporal coding, as found in the locust olfactory system.
Theoretical work on Sparse distributed memory has suggested that sparse coding increases the capacity of associative memory by reducing overlap between representations.
After this update \ mathbf { D } is renormalized to fit the constraints and the new sparse coding is obtained again.
However, in 2007, Quiroga, Kreiman, Koch and Fried rescinded their initial views, trying to explain their results with sparse coding
The idea of sparse coding is that very small numbers of neurons respond to specific features, objects or concepts in an obvious manner.
In a recent article Quiroga, Kreiman, Koch and Fried admitted they had in fact not found grandmother cells, rather they had found sparse coding.
This information favors sparse coding over grandmother cells, because the neurons fire only to very few stimuli, and are mostly silent with the exception of their preferred stimuli.
The problem of finding an optimal sparse coding R with a given dictionary \ mathbf { D } is known as sparse approximation ( or sometimes just sparse coding problem ).
The problem of finding an optimal sparse coding R with a given dictionary \ mathbf { D } is known as sparse approximation ( or sometimes just sparse coding problem ).

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