Nanoscale memristors can be used as synapses in brain-mimicking neuromorphic systems. Here, the fine tuning of memristor conductance is important in controlling the synapse weights precisely, because the coarse tuning of memristor synapses can cause a significant error in neuromorphic processing. In this paper, we propose a new Pulse Amplitude Modulation (PAM) method for the fine tuning of memristor conductance. The new PAM scheme is verified by the experimental measurement of real memristors, where the new PAM could reduce the pulse-to-pulse fluctuation in conductance change per pulse by 84.8%, compared to the previous linear PAM. For comparing the linear and new PAM schemes, they are tested in programming memristor synapses in the memristor-based Cellular Neural Networks (CNN). The simulation result confirms that the new-PAM-programmed CNN shows better quality of edge detection than the linear-PAM-programmed CNN.
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Atomic and Molecular Physics, and Optics
- Condensed Matter Physics
- Surfaces, Coatings and Films
- Electrical and Electronic Engineering