Details
![Ichiro Kawashima Headshot](https://confcats-catavault.s3.amazonaws.com/CATAVault/ieeecass/master/files/styles/cc_user_photo/s3/user-pictures/11821.png?h=74676c23&itok=DpjVzfEV)
- Affiliation
-
AffiliationKyushu Institute of Technology
- Country
Artificial general intelligence, which imitates the human brain, is aspired. Episodic memories are considered to be a key feature in building human brain functions. This paper proposes a memory-based entorhinal-hippocampal model that encodes spatial and non-spatial information, essential to realize episodic memories. The model works as a memory that stores the location of objects and events as neural activity packets. This paper also proposes an area-efficient hardware implementation method for field-programmable gate arrays (FPGAs). Our proposal utilizes on-chip random access memories (RAMs) to achieve a large-scale implementation of our model. Circuit simulations validated the behavior of our hardware-friendly model. The results of logic synthesis revealed the area efficiency of the FPGA implementation method that utilizes on-chip RAMs.