FPGA based singular value decomposition for image processing applications

During last decades, singular value decomposition has been widely used in different fields of engineering and science. This makes SVD calculation algorithms and its feasible implementations, an attractive area of research. FPGA implementation of SVD is addressed in some past publications, however, a...

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Main Authors: Rahmati, M., Sadri, M.S., Naeini, M.A.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Field programmable gate arrays
Generators
Jacobian matrices
Magnetic cores
Mathematical model
Table lookup
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Sadri, M.S.
Naeini, M.A.
description During last decades, singular value decomposition has been widely used in different fields of engineering and science. This makes SVD calculation algorithms and its feasible implementations, an attractive area of research. FPGA implementation of SVD is addressed in some past publications, however, appearance of new primary elements such as dedicated hardware multipliers, block memories and CPU cores inside new FPGA products, such as Xilinx Virtex-4, made it possible to use them in more complicated computation tasks.
doi_str_mv 10.1109/ASAP.2008.4580176
format conference_proceeding
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subjects Accuracy
Field programmable gate arrays
Generators
Jacobian matrices
Magnetic cores
Mathematical model
Table lookup
title FPGA based singular value decomposition for image processing applications
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