Algorithms for Efficient Computation of Convolution

C 2013

Algorithms for Efficient Computation of Convolution

KARAS, Pavel a David SVOBODA

Základní údaje

Originální název

Algorithms for Efficient Computation of Convolution

Název česky

Algoritmy pro efektivní výpočet konvoluce

Autoři

KARAS, Pavel a David SVOBODA

Vydání

1st ed. Rijeka (CRO), Design and Architectures for Digital Signal Processing, od s. 179-208, 30 s. 2013

Nakladatel

InTech

Další údaje

Jazyk

angličtina

Typ výsledku

Kapitola resp. kapitoly v odborné knize

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Chorvatsko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/13:00065930

Organizační jednotka

Fakulta informatiky

ISBN

978-953-51-0874-0

DOI

https://doi.org/10.5772/3456

Klíčová slova česky

konvoluce; algoritmy; FFT; separabilní konvoluce; rekurzivní filtry; paralelizace; dekompozice

Klíčová slova anglicky

convolution; algorithms; FFT; separable convolution; recursive filters; parallelization; decomposition

Štítky

cbia-web

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 28. 4. 2014 11:28, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Convolution is an important mathematical tool in both fields of signal and image processing. It is em-ployed in filtering, denoising, edge detection, correlation, compression, deconvolution, simulation, and in many other applications. Although the concept of convolution is not new, the efficient computation of convolution is still an open topic. As the amount of processed data is constantly increasing, there is considerable request for fast manipulation with huge data. Moreover, there is demand for fast algorithms which can exploit computational power of modern parallel architectures. The aim of this chapter is to review the algorithms and approaches for computation of convolution with regards to various properties such as signal and kernel size or kernel separability (when pro-cessing n-dimensional signals). Target architectures include superscalar and parallel processing units (namely CPU, DSP, and GPU), programmable architectures (e.g. FPGA), and distributed systems (such as grids). The structure of the chapter is designed to cover various applications with respect to the signal size, from small to large scales.

Návaznosti

GBP302/12/G157, projekt VaV

Název: Dynamika a organizace chromosomů během buněčného cyklu a při diferenciaci v normě a patologii

Investor: Grantová agentura ČR, Dynamika a organizace chromosomů během buněčného cyklu a při diferenciaci v normě a patologii

MUNI/A/0760/2012, interní kód MU

Název: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace II. (Akronym: FI MAV II.)

Investor: Masarykova univerzita, Rozsáhlé výpočetní systémy: modely, aplikace a verifikace II., DO R. 2020_Kategorie A - Specifický výzkum - Studentské výzkumné projekty

MUNI/A/0914/2009, interní kód MU

Název: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace (Akronym: SV-FI MAV)

Investor: Masarykova univerzita, Rozsáhlé výpočetní systémy: modely, aplikace a verifikace, DO R. 2020_Kategorie A - Specifický výzkum - Studentské výzkumné projekty

Citovat

KARAS, Pavel a David SVOBODA. Algorithms for Efficient Computation of Convolution. In Design and Architectures for Digital Signal Processing. 1st ed. Rijeka (CRO): InTech, 2013, s. 179-208. ISBN 978-953-51-0874-0. Dostupné z: https://doi.org/10.5772/3456.

@inbook{992722,
   author = {Karas, Pavel and Svoboda, David},
   address = {Rijeka (CRO)},
   booktitle = {Design and Architectures for Digital Signal Processing},
   doi = {https://doi.org/10.5772/3456},
   edition = {1st ed.},
   keywords = {convolution; algorithms; FFT; separable convolution; recursive filters; parallelization; decomposition},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Rijeka (CRO)},
   isbn = {978-953-51-0874-0},
   pages = {179-208},
   publisher = {InTech},
   title = {Algorithms for Efficient Computation of Convolution},
   url = {http://www.intechopen.com/books/design-and-architectures-for-digital-signal-processing/algorithms-for-efficient-computation-of-convolution},
   year = {2013}
}

TY  - CHAP
ID  - 992722
AU  - Karas, Pavel - Svoboda, David
PY  - 2013
TI  - Algorithms for Efficient Computation of Convolution
VL  - Neuveden
PB  - InTech
CY  - Rijeka (CRO)
SN  - 9789535108740
KW  - convolution
KW  - algorithms
KW  - FFT
KW  - separable convolution
KW  - recursive filters
KW  - parallelization
KW  - decomposition
UR  - http://www.intechopen.com/books/design-and-architectures-for-digital-signal-processing/algorithms-for-efficient-computation-of-convolution
L2  - http://www.intechopen.com/books/design-and-architectures-for-digital-signal-processing/algorithms-for-efficient-computation-of-convolution
N2  - Convolution is an important mathematical tool in both fields of signal and image processing. It is em-ployed in filtering, denoising, edge detection, correlation, compression, deconvolution, simulation, and in many other applications. Although the concept of convolution is not new, the efficient computation of convolution is still an open topic. As the amount of processed data is constantly increasing, there is considerable request for fast manipulation with huge data. Moreover, there is demand for fast algorithms which can exploit computational power of modern parallel architectures. The aim of this chapter is to review the algorithms and approaches for computation of convolution with regards to various properties such as signal and kernel size or kernel separability (when pro-cessing n-dimensional signals). Target architectures include superscalar and parallel processing units (namely CPU, DSP, and GPU), programmable architectures (e.g. FPGA), and distributed systems (such as grids). The structure of the chapter is designed to cover various applications with respect to the signal size, from small to large scales.
ER  -

KARAS, Pavel a David SVOBODA. Algorithms for Efficient Computation of Convolution. In \textit{Design and Architectures for Digital Signal Processing}. 1st ed. Rijeka (CRO): InTech, 2013, s.~179-208. ISBN~978-953-51-0874-0. Dostupné z: https://doi.org/10.5772/3456.

Přehled o publikaci