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Second Order Dimensionality Reduction Using Minimum and Maximum Mutual Information Models
Conventional methods used to characterize multidimensional neural feature selectivity, such as spike-triggered covariance (STC) or maximally informative dimensions (MID), are limited to Gaussian stimuli or are only able to identify a small number of features due to the curse of dimensionality. To ov...
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| 主要な著者: | , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2011
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3203063/ https://ncbi.nlm.nih.gov/pubmed/22046122 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1002249 |
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