ReI

Repositorio Institucional del ITESO

Yield optimization of microwave circuits using neural space mapping methods

Manakin: DSpace XMLUI Project v2

Mostrar el registro sencillo del ítem

dc.contributor.author Rayas-Sánchez, José E.
dc.contributor.author Bandler, John W.
dc.date.accessioned 2013-05-21T15:23:31Z
dc.date.available 2013-05-21T15:23:31Z
dc.date.issued 2003-07
dc.identifier.citation J. E. Rayas-Sánchez and J. W. Bandler, “Yield optimization of microwave circuits using neural space mapping methods,” in 3rd Annual McMaster Optimization Conference: Theory and Applications (MOPTA 03), Hamilton, ON, July 2003. es
dc.identifier.uri http://hdl.handle.net/11117/587
dc.description Electromagnetic (EM) simulators are regarded as highly accurate to predict the behavior of microwave circuits. With the increasing availability of commercial EM field solvers, it is very desirable to include them in the statistical analysis and yield-driven design of high speed circuits. Given the high cost in computational effort imposed by EM simulators, smart procedures must be searched to efficiently use them for statistical analysis and design. Artificial Neural Networks (ANN) and Space Mapping (SM) have been efficiently combined to formulate EM-based design algorithms. We describe in this work the use of neural space mapping methods for efficient and accurate EM-based statistical analysis and yield optimization of high frequency electronic structures. We formulate the yield optimization problem using SMbased neuromodels, which can be obtained either from a modeling process or from a design process. The SM-based neuromodel combines the computational efficiency of coarse models (typically equivalent circuit models) with the accuracy of fine models (typically EM simulators). The statistical analysis and design is realized in the frequency domain. A general equation to express the relationship between the fine and coarse model sensitivities through a nonlinear, frequency-sensitive neuromapping is reviewed. We describe the use of SM-based neuromodels for symmetric and asymmetric variations in the tolerances of the physical design parameters. We illustrate our technique by the yield analysis and optimization of a high-temperature superconducting (HTS) quarter-wave parallel coupledline microstrip filter. es
dc.description.sponsorship ITESO, A.C. es
dc.language.iso eng es
dc.publisher 3rd Annual McMaster Optimization Conference: Theory and Applications es
dc.relation.ispartofseries Annual McMaster Optimization Conference: Theory and Applications;3rd
dc.rights.uri http://quijote.biblio.iteso.mx/licencias/CC-BY-NC-ND-2.5-MX.pdf es
dc.subject Neural Space Mapping (NSM) es
dc.subject Microwave Circuits es
dc.title Yield optimization of microwave circuits using neural space mapping methods es
dc.type info:eu-repo/semantics/conferencePaper es
rei.revisor 3rd Annual McMaster Optimization Conference: Theory and Applications (MOPTA 03)
rei.peerreviewed Yes es


Archivos en el ítem

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

Buscar en todo


Listar

Mi cuenta