Fully analog memristive circuits for optimization tasks: a comparison
Forrest C. Sheldon, Francesco Caravelli, Carleton Coffrin
TL;DR
This paper introduces a Lyapunov function for memristive circuits and compares their optimization effectiveness to software across three problem classes, demonstrating rapid extremization capabilities.
Contribution
It presents a novel Lyapunov function for memristive circuit dynamics and provides a comparative analysis with traditional optimization software.
Findings
Memristors effectively extremize the targeted functionals.
Memristive circuits perform competitively with software in optimization tasks.
The approach demonstrates rapid convergence in embedded problem classes.
Abstract
We introduce a Lyapunov function for the dynamics of memristive circuits, and compare the effectiveness of memristors in minimizing the function to widely used optimization software. We study in particular three classes of problems which can be directly embedded in a circuit topology, and show that memristors effectively attempt at (quickly) extremizing these functionals.
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