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Mathematical Object

Rectified Linear Unit

Computation, Optimization and Control

In the context of artificial neural networks, the rectifier, or ReLU for rectified linear unit, is an activation function defined as the non-negative part of its input, equal to the input itself when the input is positive and to zero otherwise, a shape sometimes called a ramp function. This behavior is analogous to half-wave rectification in electrical engineering, and ReLU has become one of the most popular activation functions used in artificial neural networks, with applications in computer vision, speech recognition through deep neural networks, and computational neuroscience. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/

Facts
Classification
Object Kind
Function 1
Connections

Is Kind Of Object

Functions, Concepts

Entity-backed identity for the object-kind enum value this mathematical object already carries, resolved to a mathematics concept by an explicit value-to-entity map (phase 3 bucket conversion, docs\design_entity_backed_browse_buckets_20260928.md). The object-kind fact itself stays on the object unchanged.

Sources
1. Rectified Linear Unit (Wikipedia)
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