TY - GEN
T1 - Cellular neural network computational scheme for efficient implementation of the FDTD method
AU - Mayor, Juan
AU - Tobon, Luis
AU - Nagy, Zoltan
AU - Tamura, Eugenio
PY - 2013
Y1 - 2013
N2 - A Cellular Neural Network (CNN) computational scheme is a processor array structure that emulates the most valuable parallelizing capabilities of the Artificial Neural Network (ANN) (L. Chua, L. Yang, Circuits and Systems, IEEE Tran, 1988). Each cell or processor inside the array has a specific processing capabilities depending on the mapped numerical application over it. This scheme has been proved in different applications that assure a PDE regular mesh mapping (A. Kiss, Z. Nagy, Journal of Circuit Theory and App, 2008).
AB - A Cellular Neural Network (CNN) computational scheme is a processor array structure that emulates the most valuable parallelizing capabilities of the Artificial Neural Network (ANN) (L. Chua, L. Yang, Circuits and Systems, IEEE Tran, 1988). Each cell or processor inside the array has a specific processing capabilities depending on the mapped numerical application over it. This scheme has been proved in different applications that assure a PDE regular mesh mapping (A. Kiss, Z. Nagy, Journal of Circuit Theory and App, 2008).
UR - http://www.scopus.com/inward/record.url?scp=84894201247&partnerID=8YFLogxK
U2 - 10.1109/USNC-URSI.2013.6715385
DO - 10.1109/USNC-URSI.2013.6715385
M3 - Conference contribution
AN - SCOPUS:84894201247
SN - 9781479911295
T3 - 2013 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2013 - Proceedings
SP - 79
BT - 2013 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2013 - Proceedings
T2 - 2013 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), USNC-URSI 2013
Y2 - 7 July 2013 through 13 July 2013
ER -