Cognitive Applications in Resistive Memories

The upcoming trends in information technology follow irresistibly the predicted changes of the Internet of Things (IoT). That requires enhanced performance of mobile electronics, thus memory techniques face a growing number of challenges. Redox-based resistive switches (ReRAM) are highly attractive devices for implementation of ultimately-scaled energy-efficient memories. In this thesis, associative memories and sorting networks based on resistive switches are investigated. These cognitive functions highlight the potential of brain inspired computing in memory and are considered as a key-enabler for beyond von-Neumann computer architectures.