Show simple item record

dc.creatorSwidzinski, Jan
dc.date.accessioned2012-06-07T22:50:45Z
dc.date.available2012-06-07T22:50:45Z
dc.date.created1997
dc.date.issued1997
dc.identifier.urihttp://hdl.handle.net/1969.1/ETD-TAMU-1997-THESIS-S95
dc.descriptionDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item.en
dc.descriptionIncludes bibliographical references: p.99-104.en
dc.descriptionIssued also on microfiche from Lange Micrographics.en
dc.description.abstractThe objective of this thesis is to develop efficient methodologies for statistical behavioral modeling of analog integrated circuits and apply them to practical problems. Through appropriate statistical modeling, the Design for Quality (DFQ) of large analog integrated circuits can be realized. Various problems related to the statistical modeling of integrated circuits are discussed and solutions are presented. Several topics are addressed: statistical characterization and modeling of CMOS transistors, statistical i-nodeling techniques for integrated circuits, statistical behavioral modeling of analog functional blocks, and finally statistical behavioral system level modeling and simulation. A full statistical model for the behavioral parameters of an analog cell is presented. Behavioral parameter variations with respect to manufacturing process disturbances are approximated utilizing multivariate modeling techniques which allow the means, standard deviations, parameter correlations and the actual distributions to be reproduced with reasonable accuracy. Behavioral parameters can be characterized from measurements or from circuit simulation of the analog cell. Efficient statistical methods for characterization of the behavioral space are demonstrated. By combining the statistical models with an Analog Hardware Description Language (AHDL) we include statistical information in the behavioral model. Such models can then be used for simulation and yield estimation at a higher level of circuit abstraction. This procedure is demonstrated in statistical behavioral modeling of a MOSFETC notch filter, analog multiplier at the cell level, and a phase-locked loop (PLL) tunable filter at the system level. characterized behavioral MOSFET-C filter and the PLL models, relative to the circuit-level simulation is considered. The major contribution of this thesis is the improvement/application and development of three general classes of statistical modeling strategies. The first class, Basic Additive Modeling-Model (A), originally proposed in [2], where three levels of models which vary from the simple linear regression model to the complex hierarchical one, are demonstrated. The second class called Direct Modeling- Model (B), utilizes regression analysis in conjunction with the first-order sensitivity matrix based parameter screening, obtained through Propagation of Variance (POV) technique. Finally, the third technique, Reduced Space Modeling-Model (C) combines an innovative inverse Y-space mapping concept with the multivariate modeling techniques such as Principal Component Analysis and Factor Analysis. Systematic procedures for the statistical simulation of system level designs in the behavioral environment are also developed. Methodologies and statistical behavioral models developed in this thesis were subject to extensive testing which showed that the statistical design process can become more practical if such techniques are adopted.en
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.subjectelectrical engineering.en
dc.subjectMajor electrical engineering.en
dc.titleMethodologies for statistical behavioral modeling and simulation of complex analog integrated circuitsen
dc.typeThesisen
thesis.degree.disciplineelectrical engineeringen
thesis.degree.nameM.S.en
thesis.degree.levelMastersen
dc.type.genrethesisen
dc.type.materialtexten
dc.format.digitalOriginreformatted digitalen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

This item and its contents are restricted. If this is your thesis or dissertation, you can make it open-access. This will allow all visitors to view the contents of the thesis.

Request Open Access