Neuromorphic systems, which aim to mimic the function of the biological brain, are promising candidates to overcome the Von Neumann architecture. Traditional architectures, where memory and processing unit are separated, cannot withstand the exponential growth of computation power and data transfer rate requirements. The attractiveness of biological neural networks is the ability to concurrently work both as computing and storage unit. In this context, memristors are increasingly gaining interest as artificial neurons or synaptic elements thanks to their low power consumption, scalability and CMOS technology compatibility. Memristors are two-terminal devices consisting of two electrodes sandwiching a switching layer. By applying a voltage across the two terminals, the resistance of the device can be changed from low (ON state) to high (OFF state) and vice-versa.