Descriptor English: | Neural Networks, Computer | ||||||
Descriptor Spanish: |
Redes Neurales de la Computación
| ||||||
Descriptor Portuguese: | Redes Neurais de Computação | ||||||
Descriptor French: | Without translation | ||||||
Entry term(s): |
Computational Neural Network Computational Neural Networks Computer Neural Network Computer Neural Networks Connectionist Model Connectionist Models Model, Connectionist Model, Neural Network Models, Connectionist Models, Neural Network Network Model, Neural Network Models, Neural Network, Computational Neural Network, Computer Neural Network, Neural (Computer) Networks, Computational Neural Networks, Computer Neural Networks, Neural (Computer) Neural Network (Computer) Neural Network Model Neural Network Models Neural Network, Computational Neural Network, Computer Neural Networks (Computer) Neural Networks, Computational Perceptron Perceptrons |
||||||
Tree number(s): |
G17.485 L01.224.050.375.605 |
||||||
RDF Unique Identifier: | https://id.nlm.nih.gov/mesh/D016571 | ||||||
Scope note: | A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming. |
||||||
Annotation: | do not confuse with NEURAL NETWORKS (ANATOMIC) see NERVE NET |
||||||
Allowable Qualifiers: | No qualifiers | ||||||
Previous Indexing: |
Artificial Intelligence (1987-1991) Computer Simulation (1987-1991) Image Processing, Computer-Assisted (1990-1991) |
||||||
Public MeSH Note: | 2020; was NEURAL NETWORKS (COMPUTER) 1992-2019 |
||||||
History Note: | 2020 (1992); was NEURAL NETWORKS (COMPUTER) 1992-2019 |
||||||
DeCS ID: | 29935 | ||||||
Unique ID: | D016571 | ||||||
NLM Classification: | WL 26.5 | ||||||
Documents indexed in the Virtual Health Library (VHL): | Click here to access the VHL documents | ||||||
Date Established: | 1992/01/01 | ||||||
Date of Entry: | 1991/01/25 | ||||||
Revision Date: | 2019/01/18 |
-
-
PHENOMENA AND PROCESSES
Mathematical Concepts [G17]Mathematical Concepts -
INFORMATION SCIENCE
Information Science [L01]Information Science
|
Neural Networks, Computer
- Preferred
Concept UI |
M0025278 |
Scope note | A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming. |
Preferred term | Neural Networks, Computer |
Entry term(s) |
Computational Neural Network Computational Neural Networks Computer Neural Network Computer Neural Networks Connectionist Model Connectionist Models Model, Connectionist Model, Neural Network Models, Connectionist Models, Neural Network Network Model, Neural Network Models, Neural Network, Computational Neural Network, Computer Neural Network, Neural (Computer) Networks, Computational Neural Networks, Computer Neural Networks, Neural (Computer) Neural Network (Computer) Neural Network Model Neural Network Models Neural Network, Computational Neural Network, Computer Neural Networks (Computer) Neural Networks, Computational Perceptron Perceptrons |
We want your feedback on the new DeCS / MeSH website
We invite you to complete a survey that will take no more than 3 minutes.
Go to survey