2024/09/21 by Anne-Men Huijzer, Arjan van der Schaft, Bart Besselink · 2 citations
Engineering · Neuroscience · #Advanced Memory and Neural Computing #Artificial intelligence #Computer science #Control (management) #Control engineering #Control theory (sociology) #Electrical engineering #Electronic engineering #Engineering #Memistor #Memristor #Neural dynamics and brain function #Neuroscience and Neural Engineering #Resistive random-access memory
paper · doi:10.1016/j.automatica.2024.111922
openalex publication_date 2024/09/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
This paper presents a mathematical framework for the modelling and analysis of networks of memristors, where we describe a memristor as a monotone relation between electric charge and magnetic flux. Using this framework, we show that the port behaviour of networks of monotone memristors can equivalently be described by a single monotone memristor, the so-called effective memristor. The behaviour of the effective memristor is influenced by the monotonicity properties of the single memristors and the structure of the network of memristors. An algorithm is provided to derive an explicit characterisation of the effective memristor of any network of memristors. In addition, explicit bounds on the effective memristance curve are derived in terms of the effective resistance of associated resistor networks. Finally, an explicit description of the port behaviour of series and parallel interconnections is derived and simulation examples are provided for two simple circuits.