Neural Comput - What is the limit of redundancy reduction with divisive normalization?

Tópicos

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Resumo

Divisive normalization has been proposed as a nonlinear redundancy reduction mechanism capturing contrast correlations. Its basic function is a radial rescaling of the population response. Because of the saturation of divisive normalization, however, it is impossible to achieve a fully independent representation. In this letter, we derive an analytical upper bound on the inevitable residual redundancy of any saturating radial rescaling mechanism.

Resumo Limpo

divis normal propos nonlinear redund reduct mechan captur contrast correl basic function radial rescal popul respons satur divis normal howev imposs achiev fulli independ represent letter deriv analyt upper bound inevit residu redund satur radial rescal mechan

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