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STDP learning rule based on memristor with STDP property

机译:基于具有STDP属性的忆阻器的STDP学习规则

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Spike-timing-dependent plasticity (STDP) learning ability has been observed in physical memristors, but whether the STDP is caused by the neuron or the memristor is unclear. In this paper, we proved the STDP property in the model for both symmetric and asymmetric memristor. We also employed the symmetric/asymmetric memristors with STDP property and the simplified neurons to perform the STDP learning ability. At last, the sequence learning experiment of the memritive neural network (MNN) with the symmetric memristor synapse further verifies the STDP learning ability of the memristor.
机译:在物理忆阻器中已经观察到了依赖于尖峰时序的可塑性(STDP)学习能力,但是尚不清楚STDP是由神经元引起还是由忆阻器引起。在本文中,我们证明了对称忆阻器和非对称忆阻器模型的STDP性质。我们还采用具有STDP属性的对称/不对称忆阻器和简化的神经元来执行STDP学习能力。最后,对具有对称忆阻器突触的记忆神经网络(MNN)进行序列学习实验,进一步验证了忆阻器的STDP学习能力。

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