TY - CHAP A1 - Ping Hu A2 - Shuxiang Wu A3 - Shuwei Li ED1 - Calin Ciufudean Y1 - 2018-10-03 PY - 2018 T1 - Synaptic Behavior in Metal Oxide-Based Memristors N2 - Nowadays, scientific research deals with alternative solutions for creating non-traditional computing systems, such as neural network architectures where the stochastic nature and live dynamics of memristive models play a key role. The features of memristors make it possible to direct processing and analysis of both biosystems and systems driven by artificial intelligence, as well as develop plausible physical models of spiking neural networks with self-organization. This book deals with advanced applications illustrating these concepts, and delivers an important contribution for the achievement of the next generation of intelligent hybrid biostructures. Different modeling and simulation tools can deliver an alternative to funding the theoretical approach as well as practical implementation of memristive systems. BT - Advances in Memristor Neural Networks SP - Ch. 1 UR - https://doi.org/10.5772/intechopen.78408 DO - 10.5772/intechopen.78408 SN - 978-1-78984-116-9 PB - IntechOpen CY - Rijeka Y2 - 2022-05-17 ER -