McCulloch-Pitts Neuron Model
GPTKB entity
Properties (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
neural network model
|
| gptkbp:basedOn |
binary threshold logic
|
| gptkbp:composedOf |
weights
activation function inputs |
| gptkbp:description |
a simplified representation of a neuron
|
| gptkbp:developedBy |
gptkb:Warren_McCulloch
gptkb:Walter_Pitts |
| gptkbp:hasCitations |
assumes binary inputs and outputs
does not model biological neurons accurately |
| gptkbp:hasInfluenceOn |
modern neural networks
computational models of cognition deep learning architectures |
| gptkbp:hasRelatedPatent |
control systems
signal processing data classification pattern recognition |
| https://www.w3.org/2000/01/rdf-schema#label |
McCulloch-Pitts Neuron Model
|
| gptkbp:influencedBy |
Boolean algebra
|
| gptkbp:introduced |
1943
|
| gptkbp:isAssociatedWith |
information theory
Turing machines cybernetics logic circuits |
| gptkbp:isConsidered |
a foundational concept in AI
a model for understanding computation in the brain a precursor to modern neural networks |
| gptkbp:isCriticizedFor |
lack of learning capability
limited representation of neural networks not accounting for synaptic dynamics oversimplification of neuron behavior |
| gptkbp:isExploredIn |
academic research
philosophy of mind neuroscience literature computer science studies |
| gptkbp:isFacilitatedBy |
logical functions
|
| gptkbp:isPartOf |
artificial intelligence research
machine learning frameworks computational neuroscience |
| gptkbp:isRelatedTo |
neural computation
perceptron artificial neurons |
| gptkbp:isStudiedIn |
neural network theory
artificial intelligence ethics machine learning ethics |
| gptkbp:isUsedIn |
cognitive science
theoretical neuroscience |
| gptkbp:powerOutput |
binary values
|
| gptkbp:usedIn |
artificial intelligence
machine learning |