Scholarlink

In this study, a low-power analog integrated classifier for biomedical applications based on an ANN is introduced. The proposed architecture consists of four analog circuits as building blocks. All circuits operate in sub-threshold region in order to achieve low-power consumption. Post-layout simulations using the Cadence IC Suite and the TSMC 90 nm CMOS technology demonstrate that the proposed analog classifier operates properly with good sensitivity. The implemented classifier is trained using software and it is compared with related classifiers. It can be used as a building block for biomedical monitoring.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Low-Power Analog Neural Network Classifier for Biomedical Applications

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Andreas Papathanasiou,
  • Vassilis Alimisis,
  • Ourania Ntasiou,
  • Konstantinos Cheliotis,
  • Paul P. Sotiriadis

摘要

In this study, a low-power analog integrated classifier for biomedical applications based on an ANN is introduced. The proposed architecture consists of four analog circuits as building blocks. All circuits operate in sub-threshold region in order to achieve low-power consumption. Post-layout simulations using the Cadence IC Suite and the TSMC 90 nm CMOS technology demonstrate that the proposed analog classifier operates properly with good sensitivity. The implemented classifier is trained using software and it is compared with related classifiers. It can be used as a building block for biomedical monitoring.