This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based ...
We propose, and justify, an economic theory to guide memory system design, operation, and analysis. Our theory treats memory random-access latency, and its cost per installed mega...
In this paper we present a system that uses its underlying physiology, a hierarchical memory and a collection of memory management algorithms to learn concepts as cases and to bui...
The complexity of today’s embedded applications requires modern high-performance embedded System-on-Chip (SoC) platforms to be multiprocessor architectures. Advances in FPGA tec...