Stochastic neuro-fuzzy system implemented in memristor crossbar arrays.

ABSTRACT: Neuro-symbolic artificial intelligence has garnered considerable attention amid increasing industry demands for high-performance neural networks that are interpretable and adaptable to previously unknown problem domains with minimal reconfiguration. However, implementing neuro-symbolic hardware is challenging due to the complexity in symbolic knowledge representation and calculation. We experimentally demonstrated a memristor-based neuro-fuzzy hardware based on TiN/TaO_x/HfO_x/TiN chips that is superior to its silicon-based counterpart in terms of throughput and energy efficiency by using array topological structure for knowledge representation and physical laws for computing. Intrinsic memristor variability is fully exploited to increase robustness in kno

SUBMITTER: Shi T 

PROVIDER: S-EPMC10959402 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature