![]() These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. Finally, an activation function controls the amplitude of the output. This activity is referred to as a linear combination. ![]() All inputs are modified by a weight and summed. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. Artificial neural networks are used for solving artificial intelligence (AI) problems they model connections of biological neurons as weights between nodes. Simplified view of a feedforward artificial neural networkĪ neural network can refer to either a neural circuit of biological neurons (sometimes also called a biological neural network), or a network of artificial neurons or nodes in the case of an artificial neural network.
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