Training with states of matter search algorithm enables neuron model pruning

Artificial neural networks are machine learning systems composed of a large number of connected nodes called artificial neurons. Similar to the neurons in a biological brain, these artificial neurons are the primary basic units that are used to perform neural computations and solve problems. Advances in neurobiology have illustrated the important role played by dendritic cell structures in neural computation, and this has led to the development of artificial neuron models based on these structures.