A fault-tolerant digital artificial neuron

A simple fault-tolerant digital artificial neuron is introduced. Two digital implementations based on two different adders are examined. Reliability, fault coverage, and hardware redundancy analyses are carried out to characterize the proposed fault-tolerant digital neural module. These analyses reveal that, for a 114% increase in hardware, a 92.07% fault detection coverage and a 21.15% fault recovery coverage are attained for a four-input neural module.<
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