(Q28279493)

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A simplified neuron model as a principal component analyzer

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title

A simplified neuron model as a principal component analyzer (English)

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main subject

principal component analysis

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artificial neural network

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author

Erkki Oja

series ordinal

1

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language of work or name

English

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publication date

1982

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number of pages

7

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Journal of Mathematical Biology

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volume

15

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page(s)

267-273

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issue

3

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cites work

A theory for the acquisition and loss of neuron specificity in visual cortex

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PubMed

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https://pubmed.ncbi.nlm.nih.gov/7153672

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12 December 2020

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A logical calculus of the ideas immanent in nervous activity. 1943.

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PubMed

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https://pubmed.ncbi.nlm.nih.gov/7153672

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12 December 2020

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inferred from PubMed ID database lookup

Development of Specificity in the Cat Visual Cortex.

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PubMed

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https://pubmed.ncbi.nlm.nih.gov/7153672

retrieved

12 December 2020

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A theory for the development of feature detecting cells in visual cortex

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PubMed

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https://pubmed.ncbi.nlm.nih.gov/7153672

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12 December 2020

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Formation of topographic maps and columnar microstructures in nerve fields

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PubMed

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https://pubmed.ncbi.nlm.nih.gov/7153672

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12 December 2020

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Self-organization of orientation sensitive cells in the striate cortex

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PubMed

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https://pubmed.ncbi.nlm.nih.gov/7153672

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12 December 2020

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A physiological mechanism for Hebb's postulate of learning

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PubMed

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https://pubmed.ncbi.nlm.nih.gov/7153672

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12 December 2020

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Identifiers

DOI

10.1007/BF00275687

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Consolidated OpenCitations Corpus – April 2017

OpenCitations bibliographic resource ID

466158

Dimensions Publication ID

1041038550

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OpenCitations bibliographic resource ID

466158

1 reference

stated in

Consolidated OpenCitations Corpus – April 2017

OpenCitations bibliographic resource ID

1 reference

Consolidated OpenCitations Corpus – April 2017

OpenCitations bibliographic resource ID

466158

Springer Nature article ID

10.1007/bf00275687

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zbMATH Open document ID

0488.92012

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(Q28279493)

A simplified neuron model as a principal component analyzer

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