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المؤلفAli, Amine Ait Si
المؤلفAmira, Abbes
المؤلفBensaali, Faycal
المؤلفBenammar, Mohieddine
تاريخ الإتاحة2022-12-29T07:34:40Z
تاريخ النشر2013
اسم المنشورProceedings of the IEEE International Conference on Electronics, Circuits, and Systems
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/ICECS.2013.6815512
معرّف المصادر الموحدhttp://hdl.handle.net/10576/37782
الملخصOne of the significant stages in a gas identification system is dimensionality reduction to speed up the processing part. This is even more important when the system is implemented on a hardware platform where the resources are limited. This paper presents the design and the implementation of the learning and testing phases of principal component analysis (PCA) that can be used in a gas identification system on the heterogeneous Zynq platform. 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 computation of the eigenvectors was based on the iterative Jacobi method. The designed hardware for computing the learning part of PCA on the Zynq system on chip showed that it can be faster than its 64-bit Intel i7-3770 processor counterpart with a speed up of 1.41. Optimization techniques using HLS directives were also utilised in the hardware implementation of the testing part of the PCA to speed up the design and reduce its latency. 2013 IEEE.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعCovariance matrix
Eigenvalues and eigenfunctions
Hardware
Iterative methods
Microprocessor chips
Principal component analysis
Dimensionality reduction
Gas identification
Hardware implementations
Hardware platform
High-level synthesis
Jacobi methods
Normalization process
Optimization techniques
System-on-chip
العنوانHardware PCA for gas identification systems using high level synthesis on the Zynq SoC
النوعConference Paper
الصفحات707-710
dc.accessType Abstract Only


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