A Math Model for Ag/TiOx/FTO Memristor with Positive Photoconductance Effect

Memristors are extensively employed in neuromor-phic computing systems due to their notable advantages in nonvolatility, low power consumption, high density, and fast resistance switching. In recent years, considerable research ef-forts have been dedicated to modeling memristors with diverse structures and physical mechanisms. However, relatively fewer investigations have explored the coexistence of physical effects and resistance switching memory behaviors of memristors and their corresponding modeling approaches. This paper presents a comprehensive study on constructing a physical memristor model based on the Ag/TiOx/FTO memristor, which exhibits remarkable functionalities in optical signal sensing, information storage, and processing. Initially, the Ag/TiOx/FTO memristor is fabricated through the sol-gel method, and experimental results confirm the memristor's positive photoconductance (PPC) effect. Subsequently, an in-depth analysis of the internal principles of the memristor is conducted, facilitating the successful completion of its modeling. Moreover, based on the memristor model, a further artificial vision array is constructed, which accomplishes the functions of image perception, storage, and preprocessing, improving the efficiency and accuracy of subsequent tasks.