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Neural input space mapping optimization based on nonlinear two-layer perceptrons with optimized nonlinearity

2010; Wiley; Volume: 20; Issue: 5 Linguagem: Inglês

10.1002/mmce.20457

1096-4290

Vladimir Gutiérrez-Ayala, José E. Rayas‐Sánchez,

Neural Networks and Applications

International Journal of RF and Microwave Computer-Aided EngineeringVolume 20, Issue 5 p. 512-526 Research Article Neural input space mapping optimization based on nonlinear two-layer perceptrons with optimized nonlinearity Vladimir Gutiérrez-Ayala, Corresponding Author Vladimir Gutiérrez-Ayala vladimir.gutierrez.ayala@intel.com Intel–Guadalajara Design Center, Tlaquepaque, Jalisco, 45600 MexicoIntel – Guadalajara Design Center, Tlaquepaque, Jalisco 45600, MexicoSearch for more papers by this authorJosé E. Rayas-Sánchez, José E. Rayas-Sánchez Department of Electronics, Systems and Informatics, ITESO (Instituto Tecnológico y de Estudios Superiores de Occidente), Tlaquepaque, Jalisco, 45604 MexicoSearch for more papers by this author Vladimir Gutiérrez-Ayala, Corresponding Author Vladimir Gutiérrez-Ayala vladimir.gutierrez.ayala@intel.com Intel–Guadalajara Design Center, Tlaquepaque, Jalisco, 45600 MexicoIntel – Guadalajara Design Center, Tlaquepaque, Jalisco 45600, MexicoSearch for more papers by this authorJosé E. Rayas-Sánchez, José E. Rayas-Sánchez Department of Electronics, Systems and Informatics, ITESO (Instituto Tecnológico y de Estudios Superiores de Occidente), Tlaquepaque, Jalisco, 45604 MexicoSearch for more papers by this author First published: 28 July 2010 https://doi.org/10.1002/mmce.20457Citations: 23Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract A neural space mapping optimization algorithm based on nonlinear two layer perceptrons (2LP) is described in this article. This work is an improved version of the Neural Space-Mapping (NSM) algorithm that uses three layer perceptrons (3LP) to implement a nonlinear input mapping function at each iteration. The new version uses a nonlinear 2LP whose nonlinearity is automatically regulated with classical optimization algorithms. Additionally, the new algorithm uses a different optimization method to train the SM-based neuromodel and a more efficient manner to predict the next iterate. With these improvements, we obtain a more efficient and faster algorithm. To verify the algorithm performance, we design some synthetic circuits, as well as a stopband microstrip filter with quarter-wave resonant opens stubs, a bandpass microstrip filter, and a microstrip notch filter with mitered bends. The last three cases use commercially available full-wave electromagnetic simulators. A rigorous comparison is made with the original NSM algorithm, showing the performance improvement achieved by our proposed new formulation. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010. Citing Literature Volume20, Issue5Special Issue: Advances in Design Optimization of Microwave/RF Circuits and SystemsSeptember 2010Pages 512-526 RelatedInformation