Voltage Mode Winner-Take-All Circuit for Neuromorphic Systems

Abdullah M. Zyarah, Dhireesha Kudithipudi
7/6/2025
cs.AI

No confident code implementation found for this paper.

Abstract

Recent advances in neuromorphic computing demonstrate on-device learning capabilities with low power consumption. One of the key learning units in these systems is the winner-take-all circuit. In this research, we propose a winner-take-all circuit that can be configured to achieve k-winner and hysteresis properties, simulated in IBM 65 nm node. The circuit dissipated 34.9 $μ$W of power with a latency of 10.4 ns, while processing 1000 inputs. The utility of the circuit is demonstrated for spatial filtering and classification.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems

83% match2025

Detection of Fast-Moving Objects with Neuromorphic Hardware

82% match2024

Spike-based Neuromorphic Computing for Next-Generation Computer Vision

82% match2023

Adaptive Spiking with Plasticity for Energy Aware Neuromorphic Systems

81% match2025

Embedded FPGA Acceleration of Brain-Like Neural Networks: Online Learning to Scalable Inference

81% match2025

Topology Optimization of Random Memristors for Input-Aware Dynamic SNN

81% match1 repo52024

Cite this paper

@article{zyarah2025voltage,
  title  = {Voltage Mode Winner-Take-All Circuit for Neuromorphic Systems},
  author = {Abdullah M. Zyarah and Dhireesha Kudithipudi},
  year   = {2025},
  eprint = {2507.04338},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.04338v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2507.04338.svg)](https://codeofpaper.com/paper/2507.04338)

Discussion