Summary
International Conference on Emerging Technologies for Communications
2023
Session Number:P3
Session:
Number:P3-23
Research on Machine Learning Model for Detecting Ultrasonic Signals
Kosei Ozeki, Naofumi Aoki, Yoshinori Dobashi,
pp.-
Publication Date:2023/11/29
Online ISSN:2188-5079
Summary:
Sonic communication enables communication in environments where radio waves cannot reach. However, it is susceptible to errors caused by noise and the Doppler effect. In this paper, we simulate a sound signal degraded by white noise and frequency shift. We design a classifier using machine learning to extract information from this sound signal and demonstrate its effectiveness.