Neural Network Brain Modeling refers to the use of artificial neural networks (ANNs) to simulate the processes of the human brain. These models are designed to replicate the way neurons interact and communicate, allowing for complex patterns of information processing. Key components of these models include layers of interconnected nodes, where each node can represent a neuron and the connections between them can mimic synapses.
The primary goal of this modeling is to understand cognitive functions such as learning, memory, and perception through computational means. The mathematical foundation of these networks often involves functions like the activation function , which determines the output of a neuron based on its input. By training these networks on large datasets, researchers can uncover insights into both artificial intelligence and the underlying mechanisms of human cognition.
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