Artificial neural networks: a tutorial
Искусственные нейронные сети: учебное руководство
1996-03-01
SCID: 54.1/u8rfs6xw
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Artificial neural nets (ANNs)Artificial neural networksbiological neuroncharacter recognitionnetwork architectures
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Abstract (AI)
Artificial neural nets (ANNs) are massively parallel systems with large numbers of interconnected simple processors. The article discusses the motivations behind the development of ANNs and describes the basic biological neuron and the artificial computational model. It outlines network architectures and learning processes, and presents some of the most commonly used ANN models. It concludes with character recognition, a successful ANN application.
Key Findings
1
Artificial neural networks (ANNs) are massively parallel systems composed of many interconnected simple processors.
2
Character recognition is highlighted as a successful application of ANNs.
3
Network architectures and learning processes for ANNs are outlined, indicating systematic approaches to design and training.
4
Some of the most commonly used ANN models are presented, providing a survey of standard architectures.
5
The article describes the biological neuron and its corresponding artificial computational model as foundational to ANNs.
Research Object
Artificial neural networks (ANNs)
Research Subject
Fundamental concepts, architectures, computational neuron models, learning processes, common ANN models, and application to character recognition
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1996-03-01
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