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The use of artificial neural networks in nonlinear microwave devices and circuits modeling: An application to telecommunication system design (invited article)
Author(s) -
Harkouss Y.,
Rousset J.,
Chéhadé H.,
Ngoya E.,
Barataud D.,
Teyssier J. P.
Publication year - 1999
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/(sici)1099-047x(199905)9:3<198::aid-mmce6>3.0.co;2-a
Subject(s) - artificial neural network , nonlinear system , computer science , electronic engineering , microwave , electronic circuit , amplifier , set (abstract data type) , behavioral modeling , process (computing) , telecommunications , engineering , electrical engineering , artificial intelligence , bandwidth (computing) , operating system , quantum mechanics , programming language , physics
The design of telecommunication systems is a hierarchical process involving use of a large set of simulation tools and relying on appropriate modeling of system elements to obtain get‐it‐right‐the‐first‐time fabrication. This paper investigates in detail possible application of neural networks to modeling of large‐signal hard‐nonlinear behavior of power transistors for circuit design purpose, and modeling of nonlinear circuits such as power amplifiers for system design purpose. The problem of finding a good model is discussed through solutions offered by neural networks, with particular interest in wavelet networks trained by BFGS algorithms. Finally, experimental results are reported. ©1999 John Wiley & Sons, Inc. Int J RF and Microwave CAE 9: 198–215, 1999.