Multiple-input and multiple-output encoders with DNA-based winner-take-all neural Networks.
Journal:
Neural networks : the official journal of the International Neural Network Society
Published Date:
Sep 1, 2025
Abstract
DNA logic circuits are essential building blocks for molecular computers. Traditional molecular logic circuits primarily use basic gate circuits as computational units, achieving complex functions via multiple cascades. However, even simple logical functions often require complex cascading processes. This study introduces Winner-take-all (WTA) neural networks based on DNA strand displacement, harnessing neural networks' powerful computational capabilities for solving nonlinear complex problems. We developed multifunctional encoder circuits for two-bit and three-bit outputs and extended this design into a universal encoder circuit model. Furthermore, by cascading two DNA WTA neural networks, we successfully constructed a two-layer neural network that implements a four-bit priority encoder circuit. Simulations were performed and validated using Visual DSD software. Experimental results reveal the significant potential of DNA neural networks for building ultra-large-scale molecular logic circuits. This study offers fresh perspectives on the functionality of DNA neural networks and proposes a novel methodology for constructing complex molecular logic circuits.
