Design and Application of Brain-Inspired Circuit With Context-Dependent and State-Dependent Memory

Abstract

The context and the state of mind are important retrieval cues for long-term memory, which helps information to be retrieved quickly. However, most memristive circuits focus on the process of information memory, few studies consider the process of information retrieval. In this work, a brain-inspired circuit with context-dependent and state-dependent memory is proposed based on the three-level processing model of memory information, which integrates the processes of information memory and information retrieval. The circuit includes sensory memory module, short-term memory module, long-term memory module, information retrieval module, status module, and context module. In the circuit, information, contexts, and states are eventually transferred to long-term memory module for storage and retrieval. Meanwhile, the factors influencing information retrieval are considered, such as the degree of information memory, the time interval between information memory and retrieval, the context, and the state. And the proposed circuit has scalability, which realizes the memory of information in multiple contexts. Finally, based on the characteristics of memristors, the proposed circuit is extended for detecting damage to the machining accuracy of the mobile CNC lathe. Combining brain-inspired circuits with human memory mechanism, this work provides further reference for the research of brain-like intelligence.