Fir filter design by convex optimization using rank refinement

Simple item page
buir.supervisorArıkan, Orhan
dc.contributor.authorDedeoğlu, Mehmet
dc.date.accessioned2016-01-08T20:02:46Z
dc.date.available2016-01-08T20:02:46Z
dc.date.copyrightdc.date.issued
dc.date.issued2014
dc.descriptionAnkara : The Department of Electrical and Electronics Engineering and The Graduate School of Engineering and Science of Bilkent Univesity, 2014.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2014.en_US
dc.descriptionIncludes bibliographical references (leaves 69-75).en_US
dc.descriptionCataloged from PDF version of article.
dc.description.abstractFinite impulse response filters have been one of the primary topics of digital signal processing since their inception. Consequently, diverse class of design techniques including Chebyshev approximation, Fast Fourier Transform and optimization based methods had been proposed in the literature. With developments in com- putational tools, new design technique tools and formulations on filters including interior-point solvers and semidefinite programming (SDP), emerged. Since FIR filter design problem can be modelled as a quadratically constrained quadratic program, filter design problem can be solved via interior-point based convex op- timization methods such as semidefinite programming. Unfortunately, SDP for- mulation of problem is nonconvex due to positive lower limit constraint in the passband. To overcome that problem, nonconvex problem can be cast into a convex SDP using semidefinite relaxation, which can be solved in polynomial time. Since relaxed formulation does not guarantee rank-1 solution matrix, re- cently proposed directed iterative rank refinement (DIRR) algorithm is used to impose a convex rank-1 constraint. Due to utilization of semidefinite relaxation and DIRR, addition of various constraints, such as phase and group delay masks, in convex manner is made possible. For feasibility type optimization formulations of filter design problem, a convergence rate improved version of DIRR is devel- oped. Proposed techniques are applied on filter design problems with different set of constraints including phase and group delay constraints. Explicit simulations demostrate that the proposed technique is capable of solving nonlinear phase, phase constrained, and group delay constrained filter design problems.
dc.description.provenanceMade available in DSpace on 2016-01-08T20:02:46Z (GMT). No. of bitstreams: 0en
dc.description.statementofresponsibilityby Mehmet Dedeoğluen_US
dc.format.extentxiv, 80 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB149290
dc.identifier.urihttp://hdl.handle.net/11693/16900
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectConvex optimization
dc.subjectFIR filter design
dc.subjectSemidefinite programming
dc.subjectSemidefinite relaxation
dc.subjectIterative rank refinement
dc.subjectSpectral mask
dc.titleFir filter design by convex optimization using rank refinementen_US
dc.title.alternativeKerte arıtımı ile dışbükey eniyileme tabanlı fır süzgeç tasarımı
dc.typeThesisen_US
thesis.degree.disciplineElectrical and Electronic Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
B149290.pdf
Size:
1.17 MB
Format:
Adobe Portable Document Format
Download

Collections

Graduate School of Engineering and Science