An experimental associative capacitive network based on complementary resistive switches for memory-intensive computing

Resistive Random Access Memory (RRAM) is a promising candidate for future beyond Flash-technology memories. Beside memory applications RRAM provides opportunities for neural networks, e.g. assembled as a complementary resistive switch (CRS). CRS cells feature a nondestructive readout scheme which can be used as an associative capacitive network (ACN) for fully parallel pattern recognition. ACNs are versatilely usable for memory-intensive computing, network switches or for image recognition. Here the concept of those is experimentally proven on a passive capacitive network.