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AuthorAli, Amine Ait Si
AuthorAmira, Abbes
AuthorBensaali, Faycal
AuthorBenammar, Mohieddine
Available date2022-12-29T07:34:40Z
Publication Date2013
Publication Name2013 25th International Conference on Microelectronics, ICM 2013
ResourceScopus
URIhttp://dx.doi.org/10.1109/ICM.2013.6734998
URIhttp://hdl.handle.net/10576/37783
AbstractPrincipal component analysis (PCA) is a commonly used technique for data reduction in general as well as for dimensionality reduction in gas identification systems when a sensor array is being used. This paper presents the design and implementation of a complete PCA IP core for gas application on the Zynq programmable system on chip (SoC). All steps of PCA starting from the mean computation to the projection of data onto the new space, passing by the normalization process, covariance matrix and the eigenvectors computation are developed in C and synthesized using the new Xilinx VIVADO high level synthesis (HLS). The Jacobi method is used to find the eigenvectors and different approaches for the implementation of the PCA core on the heterogeneous Zynq platform are proposed. The hardware implementation of the presented PCA algorithm for a 16 x 30 matrix is faster than the software one with a speed up of 1.41 times when executed on a desktop running a 64-bit Intel i7-3770 processor at 3.40GHz. It was achieved using an average of 23% of all resources. 2013 IEEE.
Languageen
SubjectDesign and implementations
Dimensionality reduction
Hardware implementations
High-level synthesis
Jacobi methods
Normalization process
PCA algorithms
Programmable system on chips
Covariance matrix
Eigenvalues and eigenfunctions
Hardware
Microelectronics
Microprocessor chips
Principal component analysis
TitlePCA IP-core for gas applications on the heterogenous zynq platform
TypeConference Paper
dc.accessType Abstract Only


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