Abstract
Memristive devices are popular among neuromorphic engineers for their ability to emulate forms of spike-driven synaptic plasticity by applying specific voltage and current waveforms at their two terminals. In this paper, we investigate spike-timing dependent plasticity (STDP) with a single pairing of one presynaptic voltage spike and one post-synaptic voltage spike in a BiFeO3 memristive device. In most memristive materials the learning window is primarily a function of the material characteristics and not of the applied waveform. In contrast, we show that the analog resistive switching of the developed artificial synapses allows to adjust the learning time constant of the STDP function from 25 ms to 125 μs via the duration of applied voltage spikes. Also, as the induced weight change may degrade, we investigate the remanence of the resistance change for several hours after analog resistive switching, thus emulating the processes expected in biological synapses. As the power consumption is a major constraint in neuromorphic circuits, we show methods to reduce the consumed energy per setting pulse to only 4.5 pJ in the developed artificial synapses.
Highlights
Since the discovery of spike-timing dependent plasticity (STDP) in biological synapses (Bi and Poo, 1998; Snider, 2008; Di Lorenzo and Victor, 2013), scientists have been captivated by the idea of changing the synaptic weight, i.e., the strength between the pre- and post-neuron, in bioinspired electronic systems in a fashion similar to biology (Indiveri et al, 2006)
Learning Window According to the input signal scheme (Figure 3) the BFO memristor is set in the high resistance state (HRS) and in the low resistance states (LRSs) with a writing pulse amplitude of Vw = −8.0 and +8.0 V, respectively
The synaptic weight of the BFO memristor scales with the normalized potentiation current ILTP and the normalized depression current ILTD
Summary
Since the discovery of spike-timing dependent plasticity (STDP) in biological synapses (Bi and Poo, 1998; Snider, 2008; Di Lorenzo and Victor, 2013), scientists have been captivated by the idea of changing the synaptic weight, i.e., the strength between the pre- and post-neuron, in bioinspired electronic systems in a fashion similar to biology (Indiveri et al, 2006). The emulation of STDP with 60–80 pairings of Single pairing STDP in BFO-based memristor pre- and post-synaptic spikes has been shown for artificial synapses based on memristive TiOx (Seo et al, 2011; Thomas and Kaltschmidt, 2014), WOx (Chang et al, 2011), HfOx (Yu et al, 2011), GST (Kuzum et al, 2012), and on the memristive BiFeO3 (Mayr et al, 2012; Cederström et al, 2013). The synaptic weight of the memristor can be controlled by the time delay t between pre- and post-spike from the 1st layer I&F neuron (Figure 1A) (Zamarreño-Ramos et al, 2011). Due to the thermal diffusion of Ti atoms and their substitutional incorporation into the lower part of the BiFeO3 (BFO) layer during BFO thin film growth on a Pt/Ti bottom electrode, the barrier at the Pt/Ti bottom electrode is flexible
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