Ultralow Power Feature Extractor Using Switched-Capacitor-Based Bandpass Filter, Max Operator, and Neural Network Processor for Keyword Spotting-Reference-Cited by-同舟云学术

Ultralow Power Feature Extractor Using Switched-Capacitor-Based Bandpass Filter, Max Operator, and Neural Network Processor for Keyword Spotting

Published:2022 Issue: Volume:5 Page:82-85
ISSN:2573-9603
Container-title:IEEE Solid-State Circuits Letters
language:
Short-container-title:IEEE Solid-State Circuits Lett.

Author:

Fuketa Hiroshi¹^ORCID

Affiliation:

1. AI Chip Design Open Innovation Laboratory and Device Technology Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan

Funder

Japan Society for the Promotion of Science (JSPS) KAKENHI

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8011414/9677053/09748878.pdf?arnumber=9748878

Reference11 articles.

1. NS-FDN: Near-Sensor Processing Architecture of Feature-Configurable Distributed Network for Beyond-Real-Time Always-on Keyword Spotting

2. 9.9 A Background-Noise and Process-Variation-Tolerant 109nW Acoustic Feature Extractor Based on Spike-Domain Divisive-Energy Normalization for an Always-On Keyword Spotting Device

3. An Integrated Voice Recognition System

4. 0.8μW 12-bit SAR ADC sensors interface for RFID applications

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