A novel neural network for the synthesis of antennas and microwave devices.
A novel artificial neural network (SYNTHESIS-ANN) is presented, which has been designed for computationally intensive problems and applied to the optimization of antennas and microwave devices. The antenna example presented is optimized with respect to voltage standing-wave ratio, bandwidth, and frequency of operation. A simple microstrip transmission line problem is used to further describe the ANN effectiveness, in which microstrip line width is optimized with respect to line impedance. The ANNs exploit a unique number representation of input and output data in conjunction with a more standard neural network architecture. An ANN consisting of a heteroassociative memory provided a very efficient method of computing necessary geometrical values for the antenna when used in conjunction with a new randomization process. The number representation used provides significant insight into this new method of fault-tolerant computing. Further work is needed to evaluate the potential of this new paradigm.
Delgado
Heriberto Jose
HJ
Harris Corporation, Melbourne, FL 32902, USA. herb.delgado@ieee.org
Thursby
Michael H
MH
Ham
Fredric M
FM
D000465:Algorithms; D003198:Computer Simulation; D017076:Computer-Aided Design; D055590:Electromagnetic Phenomena / Q000295:instrumentation; D004867:Equipment Design / Q000379:methods*; D019544:Equipment Failure Analysis / Q000379:methods; D008872:Microwaves; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D013685:Telecommunications / Q000295:instrumentation*