What does a neural network simulate to process information?

A neural network is designed to mimic the structure and function of the human brain in order to process information efficiently. This biological inspiration is fundamental to how neural networks operate; they consist of interconnected nodes (or neurons) that work together to analyze and learn from data. Each connection has a weight that adjusts as learning progresses, similar to how synapses between neurons strengthen or weaken over time.

The layered structure of neurons in a neural network, including input, hidden, and output layers, reflects how the brain processes complex information through interconnected neurons. This allows neural networks to identify patterns and relationships in data that might not be immediately apparent, much like how the brain processes sensory input and formulates responses based on learned experiences.

The other options, while related to computing, do not accurately capture the essence of how neural networks are structured or how they function.