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An RRAM-based computing system (RCS) is an attractive hardware platform for implementing neural computing algorithms. On-line training for RCS enables hardware-based learning for a given application and reduces the additional error caused by device parameter variations. However, a high occurrence rate of hard faults due to immature fabrication processes and limited write endurance restrict the applicability...
The emerging metal-oxide resistive switching random-access memory (RRAM) devices and RRAM crossbar arrays have demonstrated their potential in enormously boosting the speed and energy-efficiency of analog matrix-vector multiplication. Unfortunately, due to the immature fabrication technology, commonly occurring Stuck-At-Faults (SAFs) seriously degrade the computational accuracy of RRAM crossbar based...
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