Artificial Neural Networks
Artificial neural networks (ANNs) are based on the idea that they can mimic the structure and function of biological neurons by using hardware components, such as circuits and wires, to replicate neurons and dendrites. These networks aim to collaborate with the human brain by forming appropriate connections. An artificial neural network is a computational model inspired by biological principles, consisting of processing units (nodes), connections, and algorithms for training and recall. Various types of neural networks exist, including Feedforward ANN, Feedback ANN, Learning Vector Quantization, and others.
Key concepts and models related to neural networks include:
- Supervised Models
- Physical Neural Networks
- Networks with Memory Models
- Recurrent Neural Networks (RNNs)
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