TY - GEN
T1 - A study on an online acceleration of automatic design of RF-DC conversion circuit using neural networks
AU - Akada, Takuma
AU - Fujimori, Kazuhiro
N1 - Publisher Copyright:
© 2021 IEICE.
PY - 2021/1/25
Y1 - 2021/1/25
N2 - The design method of RF-DC conversion circuits for wireless power transmission is discussed. The extent to which circuit properties can be estimated using convolutional neural networks is discussed in this study. In order to use an automatic design method for circuit design, it is a problem that it takes time for electromagnetic field analysis. It is shown that the proposed method may make it possible to design circuits in a realistic time.
AB - The design method of RF-DC conversion circuits for wireless power transmission is discussed. The extent to which circuit properties can be estimated using convolutional neural networks is discussed in this study. In order to use an automatic design method for circuit design, it is a problem that it takes time for electromagnetic field analysis. It is shown that the proposed method may make it possible to design circuits in a realistic time.
KW - Convolutional Neural Networks
KW - Genetic Algorithms
KW - RF-DC conversion circuit
UR - http://www.scopus.com/inward/record.url?scp=85104519834&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85104519834&partnerID=8YFLogxK
U2 - 10.23919/ISAP47053.2021.9391324
DO - 10.23919/ISAP47053.2021.9391324
M3 - Conference contribution
AN - SCOPUS:85104519834
T3 - 2020 International Symposium on Antennas and Propagation, ISAP 2020
SP - 805
EP - 806
BT - 2020 International Symposium on Antennas and Propagation, ISAP 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Symposium on Antennas and Propagation, ISAP 2020
Y2 - 25 January 2021 through 28 January 2021
ER -