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Wireless Communication: Parallel Signal Processing of a Wireless Pressure‐Sensing Platform Combined with Machine‐Learning‐Based Cognition, Inspired by the Human Somatosensory System (Adv. Mater. 8/2020)
Author(s) -
Lee GunHee,
Park JinKwan,
Byun Junyoung,
Yang Jun Chang,
Kwon Se Young,
Kim Chobi,
Jang Chorom,
Sim Joo Yong,
Yook JongGwan,
Park Steve
Publication year - 2020
Publication title -
advanced materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 10.707
H-Index - 527
eISSN - 1521-4095
pISSN - 0935-9648
DOI - 10.1002/adma.202070055
Subject(s) - somatosensory system , convolutional neural network , wireless , cognition , signal processing , signal (programming language) , computer science , deep learning , perception , artificial intelligence , neuroscience , computer hardware , digital signal processing , telecommunications , biology , programming language
Parallel signal processing and perceptual learning are two essential characteristics of the human somatosensory system. In article number 1906269, inspired by the human somatosensory system, Joo Yong Sim, Jong‐Gwan Yook, Steve Park, and co‐workers report the design of a wireless communication platform that is able to receive and differentiate multiple pressure signals simultaneously. Moreover, convolutional‐neural‐network‐based machine learning, mimicking human cognition ability, is implemented for the further optimization of the signal processing.