| 摘要 |
A resistance-changeable-memristor-based time correlation learning neuron circuit and an implementation method thereof are disclosed. According to the disclosure, switching characteristics of the resistance-changeable memristor are utilized, when two ends of the memristor are synchronously selected by two excitation signals, voltage drop capable of enabling the memristor to generate resistance change is formed at the two ends of a device, thus the connection or disconnection of a synapse is realized, the correlation or non-correlation of the two excitation signals is realized, a memory characteristic is realized, and the previous excitation signals can be repeated, so a learning goal is achieved. The resistance-changeable memristor is of simple structure and high integratable level, so that the connection of large-scale physical neuron synapses is realized so as to achieve a more complicated learning or even logic function. The present invention has a good application prospect in the neuron calculation. |
