Temat: signal processor - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Biometric speech signal processing in a system with digital signal processor
Autorzy:: Marciniak, T.
Weychan, R.
Stankiewicz, A.
Dąbrowski, A.
Powiązania:: https://bibliotekanauki.pl/articles/200794.pdf
Data publikacji:: 2014
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: biometry
speech processing
digital signal processor
Gaussian mixture models
vector quantization
Opis:: This paper presents an analysis of issues related to the fixed-point implementation of a speech signal applied to biometric purposes. For preparing the system for automatic speaker identification and for experimental tests we have used the Matlab computing environment and the development software for Texas Instruments digital signal processors, namely the Code Composer Studio (CCS). The tested speech signals have been processed with the TMS320C5515 processor. The paper examines limitations associated with operation of the realized embedded system, demonstrates advantages and disadvantages of the technique of automatic software conversion from Matlab to the CCS and shows the impact of the fixed-point representation on the speech identification effectiveness.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2014, 62, 3; 589-594
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

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

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