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Wyświetlanie 1-2 z 2
Tytuł:
High level synthesis in FPGA of TCS/RNS converter
Autorzy:
Smyk, R.
Czyżak, M.
Powiązania:
https://bibliotekanauki.pl/articles/377883.pdf
Data publikacji:
2017
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
high–level synthesis
residue number system
FPGA
C++ language
two's complement–to–residue converter
Opis:
The work presents the design process of the TCS/RNS (two's complement–to– residue) converter in Xilinx FPGA with the use of HLS approach. This new approach allows for the design of dedicated FPGA circuits using high level languages such as C++ language. Such approach replaces, to some extent, much more tedious design with VHDL or Verilog and facilitates the design process. The algorithm realized by the given hardware circuit is represented as the program in C++. The performed design experiments had to show whether the obtained structures of TCS/RNS converter are acceptable with respect to speed and hardware complexity. The other aim of the work was to examine whether it is enough to write the program in C++ with the use of basic arithmetic operators or bit–level description is necessary. Finally, we present the discussion of results of the TCS/RNS converter design in Xilinx Vivado HLS environment.
Źródło:
Poznan University of Technology Academic Journals. Electrical Engineering; 2017, 91; 143-154
1897-0737
Pojawia się w:
Poznan University of Technology Academic Journals. Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Efficient Classification of Hyperspectral Remotely Sensed Data Using Support Vector Machine
Autorzy:
Mahendra, H. N.
Mallikarjunaswamy, S.
Powiązania:
https://bibliotekanauki.pl/articles/2134051.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
support vector machine
SVM
central processing unit
CPU
digital signal processor
DSP
field programmable gate array
FPGA
high level synthesis
HLS
hardware description language
HDL
Opis:
This work present an efficient hardware architecture of Support Vector Machine (SVM) for the classification of Hyperspectral remotely sensed data using High Level Synthesis (HLS) method. The high classification time and power consumption in traditional classification of remotely sensed data is the main motivation for this work. Therefore presented work helps to classify the remotely sensed data in real-time and to take immediate action during the natural disaster. An embedded based SVM is designed and implemented on Zynq SoC for classification of hyperspectral images. The data set of remotely sensed data are tested on different platforms and the performance is compared with existing works. Novelty in our proposed work is extend the HLS based FPGA implantation to the onboard classification system in remote sensing. The experimental results for selected data set from different class shows that our architecture on Zynq 7000 implementation generates a delay of 11.26 μs and power consumption of 1.7 Watts, which is extremely better as compared to other Field Programmable Gate Array (FPGA) implementation using Hardware description Language (HDL) and Central Processing Unit (CPU) implementation.
Źródło:
International Journal of Electronics and Telecommunications; 2022, 68, 3; 609--617
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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