The logarithmic memristor-based Bayesian machine.

ABSTRACT: The demand for explainable and energy-efficient artificial intelligence (AI) systems for edge computing has led to growing interest in electronic systems dedicated to Bayesian inference. Traditional designs of such systems often rely on stochastic computing, which offers high energy efficiency but suffers from latency issues and struggles with low-probability values. Here, we introduce the logarithmic memristor-based Bayesian machine, an innovative design that leverages the unique properties of memristors and logarithmic computing as an alternative to stochastic computing. We present a prototype machine fabricated in a hybrid CMOS/hafnium-oxide memristor process. We validate the versatility and robustness of our system through experimental validation and extensive simulations in two distin

SUBMITTER: Turck C 

PROVIDER: S-EPMC11865314 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature