P2-21: Optimization of waveguide coupler for coupled-cavity TWT using Artificial Neural Network

Author

Christie, V. Latha ; Sumathy, M. ; Kumar, Lalit ; Prasad, Sheila

Author_Institution

Microwave Tube R&D Centre, Minist. of Defence, Bangalore, India

fYear

2010

fDate

18-20 May 2010

Firstpage

263

Lastpage

264

Abstract

In this present work, optimization of a Ku-band waveguide coupler for coupled-cavity traveling-wave tube waveguide coupler has been carried out using an Artificial Neural Network (ANN). The ANN model takes the cavity physical dimensions as the input and the VSWR as the output. The training data for the network has been taken from the numerical simulation using the 3D electromagnetic simulation software MAFIA. The ANN uses a 3 layer feed-forward network consisting of 60 neurons for each layer. The ANN was trained so that the simulated error will be less than 10%.

Keywords

electrical engineering computing; neural nets; travelling wave tubes; waveguide couplers; 3D electromagnetic simulation software MAFIA; Ku-band waveguide coupler; artificial neural network; coupled-cavity TWT; coupled-cavity traveling-wave tube; feedforward network; numerical simulation; Artificial neural networks; Bandwidth; Coupling circuits; Design optimization; Electromagnetic waveguides; Electron tubes; Feedforward systems; Neural networks; Numerical simulation; Training data; Artificial Neural Network; Coupled-cavity; MAFIA; Slow-wave Structure; Traveling-wave tubes;

fLanguage

English

Publisher

ieee

Conference_Titel

Vacuum Electronics Conference (IVEC), 2010 IEEE International

Conference_Location

Monterey, CA

Print_ISBN

978-1-4244-7098-3

Type

conf

DOI

10.1109/IVELEC.2010.5503501

Filename

5503501