Exploring Memristor Based Analog Design in Simscape

With conventional CMOS technologies approaching their scaling limits, researchers are actively investigating alternative technologies for ever increasing computing and mobile demand. A number of different technologies are currently being studied by different research groups. In the last decade, one-dimensional (1D) carbon nanotubes (CNT), graphene, which is a two-dimensional (2D) natural occurring carbon rolled in tubular form, and zero-dimensional (0D) fullerenes have been the subject of intensive research. In 2008, HP Labs announced a ground-breaking fabrication of memristors, the fourth fundamental element postulated by Chua at the University of California, Berkeley in 1971. In the last few years, the memristor has gained a lot of attention from the research community. In-depth studies of the memristor and its analog behavior have convinced the community that it has the potential in future nano-architectures for optimization of high-density memory and neuromorphic computing architectures. The objective of this thesis is to explore memristors for analog and mixed-signal system design using Simscape. This thesis presents a memristor model in the Simscape language. Simscape has been used as it has the potential for modeling large systems. A memristor based programmable oscillator is also presented with simulation results and characterization. In addition, simulation results of different memristor models are presented which are crucial for the detailed understanding of the memristor along with its properties