TY - GEN
T1 - Minimizing interference in satellite communications using chaotic neural networks
AU - Liu, Wen
AU - Shi, Haixiang
AU - Wang, Lipo
PY - 2007
Y1 - 2007
N2 - We solve the frequency assignment problem (FAP) in satellite communications with transiently chaotic neural networks (TCNN). The objective of this optimization problem is to minimize cochannel interference between two satellite systems by rearranging the frequency assignments. For an N-carrier-M-segment FAP problem, the TCNN consists of N x M neurons. The performance of the TCNN is demonstrated through solving a set of benchmark problems, where the TCNN finds comparative if not better solutions compared to the existing algorithms.
AB - We solve the frequency assignment problem (FAP) in satellite communications with transiently chaotic neural networks (TCNN). The objective of this optimization problem is to minimize cochannel interference between two satellite systems by rearranging the frequency assignments. For an N-carrier-M-segment FAP problem, the TCNN consists of N x M neurons. The performance of the TCNN is demonstrated through solving a set of benchmark problems, where the TCNN finds comparative if not better solutions compared to the existing algorithms.
UR - http://www.scopus.com/inward/record.url?scp=38049004999&partnerID=8YFLogxK
U2 - 10.1109/ICNC.2007.473
DO - 10.1109/ICNC.2007.473
M3 - Conference Proceeding
AN - SCOPUS:38049004999
SN - 0769528759
SN - 9780769528755
T3 - Proceedings - Third International Conference on Natural Computation, ICNC 2007
SP - 441
EP - 444
BT - Proceedings - Third International Conference on Natural Computation, ICNC 2007
T2 - 3rd International Conference on Natural Computation, ICNC 2007
Y2 - 24 August 2007 through 27 August 2007
ER -