Construct · 3 fields · 5 citations

Where does feedforward collide?

One name. Different field. Different construct. One map.

● jingle · one word, three constructs Nearest construct by meaningperceptroncompare the meanings
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Every construct on the map is compared with every other by the meaning of its definitions, and the closest one is surfaced here. The nearest construct to feedforward is perceptron.

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feedforward3 CONSTRUCTSFeedforward controlBLACK · FEEDFORWARD AMPAnticipatory contextRICHARDS · ANTICIPATIONFeedforward networkROSENBLATT · PERCEPTRON

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2026

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Control engineering

A correction sent ahead to cancel a disturbance before it reaches the output

Harold Black's 1928 patent Translating system (filed 1925) records the first documented use of feedforward in engineering: his amplifier sampled the distortion it introduced and reinjected that distortion in opposite phase to cancel it, correcting the output along the forward path rather than reacting to an error after the fact. The idea was later formalised as feedforward control, in which a measured disturbance or input drives a corrective action computed in advance from a model of the system, before the disturbance can affect the output. The referent is a correction sent ahead through an engineered signal or process, and it differs from an anticipatory context in speech, a one-way network of artificial neurons, or a manager's future-focused suggestion.[1]

Unit
A corrective input applied along the forward path, scaled to the measured disturbance
Recovery means
Not applicable
Measured by
Assessed by how much the disturbance's effect on the output is reduced compared with feedback alone

Rhetoric and communication

A context or purpose projected ahead of an utterance so the listener can follow it

The literary critic and rhetorician I. A. Richards coined feedforward in 1951 at the eighth Macy Conference on cybernetics, and elaborated it in his 1955 collection Speculative Instruments. He used it for the anticipatory counterpart to feedback in communication: the speaker or writer sets up in advance the purpose and context a listener needs, projecting forward what the audience must grasp before the message itself arrives. The referent is a purpose or context supplied ahead of an utterance in human communication, and it is unlike a corrective signal in a circuit, a one-way network of artificial neurons, or a coaching suggestion aimed at future behaviour.[2][3]

Unit
A context or purpose projected ahead of an utterance
Recovery means
Not applicable
Measured by
Described qualitatively in rhetoric and communication theory, not by a quantified measure

Neural networks and machine learning

A network in which signals flow one way, from input to output, with no loop back

Frank Rosenblatt's 1958 paper The perceptron introduced the first network of this kind: an arrangement of simple artificial neurons in which signals pass in one direction, from input units through weighted connections to output units, with no loop back. Networks built this way came to be called feedforward networks, and the multilayer version trained by backpropagation (Rumelhart, Hinton, and Williams, 1986) became a workhorse of modern machine learning. The referent is a computational graph with a single forward direction of signal flow, and it has nothing to do with a corrective signal in a circuit, a speaker's anticipatory context, or a manager's forward-looking advice.[4][5]

Unit
A layered set of weighted connections mapping an input vector to an output
Recovery means
Not applicable
Measured by
Characterised by its architecture (layers, units, weights) and its error on training and held-out data

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Nearby collisions

network4 fields · 6 citationsjingle · one word, four constructsfeedback4 fields · 5 citationsjingle · one word, four constructscontrol4 fields · 5 citationsjingle · one word, four constructs

References

  1. Black, H. S. (1928). Translating system (U.S. Patent No. 1,686,792). U.S. Patent and Trademark Office.
  2. Richards, I. A. (1951). Communication between men: The meaning of language. In H. von Foerster, M. Mead, & H. L. Teuber (Eds.), Cybernetics: Circular causal and feedback mechanisms in biological and social systems. Transactions of the eighth conference. Josiah Macy Jr. Foundation.
  3. Richards, I. A. (1955). Speculative instruments. Routledge & Kegan Paul.
  4. Rosenblatt, F. (1958). The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65(6), 386-408. https://doi.org/10.1037/h0042519
  5. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323(6088), 533-536. https://doi.org/10.1038/323533a0

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