ARTIFICIAL NEURAL NETWORKS

• “NEURONS” BECOME NODES

• AXONS BECOME “CONNECTIONS”

• SYNAPSES BECOME A TRANSFER FUNCTION

• HEBBIAN LEARNING EMPLOYED: USE IT OR LOOSE IT

• DISTRIBUTED SYSTEM: EACH NEURON IS THE SAME, IT IS THE PATTERN THAT COUNTS-HOLISTIC

• CAN BE MODELED LIKE THE THERMODYNAMIC NETWORKS

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