Hebb's rule refers to Hebb's contention that neurons within the brain that are simultaneously or successively active become associated. One type of neural network applies this rule by adjusting the mathematical weights of units that are simultaneously or successively active. The result is that consistent input gradually produces consistent output. (See Neural network.)

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