Anomaly detection, a data intensive task, is very important in wide application scenarios. Memristor has shown excellent performance in data intensive tasks. However, memristor used for anomaly detection has rarely been reported. In this Letter, a tantalum oxide (TaOx) memristive neuron device has been developed for anomaly detection application. TaOx, a CMOS compatible material, based memristor shows reliable threshold switching characteristics, which is suitable for constructing memristive neuron. Furthermore, the output frequency of the memristive neuron is found to be proportionate to the applied stimulus intensity and at an inflection point starts to decrease, namely, thresholding effect. Based on the thresholding effect of the neuron output, the application of the memristive neuron for anomaly detection has been simulated. The results indicate that the TaOx memristive neuron with thresholding effect shows better performance (98.78%) than the neuron without threshoding effect (90.89%) for anomaly detection task. This work provided an effective idea for developing memristive anomaly detection system.

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