Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms

Benjamin White; Frank Rosenblatt

doi:https://doi.org/10.2307/1419730

Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms

1963 · The American Journal of Psychology · 1,828 citations · 7 from inside this corpus

Benjamin White low, Frank Rosenblatt low

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

7 of 7 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.

this paper works it cites works citing it node size = global citations · hover for the full title

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

Self-organized formation of topologically correct feature maps→Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsLegacy edge — source detail unavailable
Extreme Learning Machine for Regression and Multiclass Classification→Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsLegacy edge — source detail unavailable
Neural Networks and the Bias/Variance Dilemma→Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsLegacy edge — source detail unavailable
Relational inductive biases, deep learning, and graph networks→Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsLegacy edge — source detail unavailable
30 years of adaptive neural networks: perceptron, Madaline, and backpropagation→Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsLegacy edge — source detail unavailable
Extreme learning machines: a survey→Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsLegacy edge — source detail unavailable
Trends in extreme learning machines: A review→Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsLegacy edge — source detail unavailable
30 years of adaptive neural networks: perceptron, Madaline, and backpropagation→Self-organized formation of topologically correct feature mapsLegacy edge — source detail unavailable
Trends in extreme learning machines: A review→Extreme learning machines: a surveyLegacy edge — source detail unavailable
Trends in extreme learning machines: A review→Extreme Learning Machine for Regression and Multiclass ClassificationLegacy edge — source detail unavailable
Relational inductive biases, deep learning, and graph networks→Neural Networks and the Bias/Variance DilemmaLegacy edge — source detail unavailable

What cites it, inside the corpus

Paper	Year	Cited
Self-organized formation of topologically correct feature maps	1982	9,582
Extreme Learning Machine for Regression and Multiclass Classification	2011	5,581
Neural Networks and the Bias/Variance Dilemma	1992	3,612
Relational inductive biases, deep learning, and graph networks	2018	2,406
30 years of adaptive neural networks: perceptron, Madaline, and backpropagation	1990	2,244
Extreme learning machines: a survey	2011	1,932
Trends in extreme learning machines: A review	2014	1,752

Links

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Topics

Neural Networks and Applications	Computer Science
Neural dynamics and brain function	Neuroscience

Is this record sound?

partial

One field of this record is missing or disagrees with another. What is shown below is what the source publishes.

supports2 author record(s) attached.
weakensNo references are recorded despite 1,828 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:53+00:00.

sha256 db1645b78a57e29a…