RTL fast convolution using the mersenne number transform
- Autores
- Bria, Oscar N.; Villagarcía Wanza, Horacio Alfredo
- Año de publicación
- 1997
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- VHDL is a versatile high level language for the specification and simulation of hardware components. Here a functional VHDL model is presented for performing fast convolution based on Mersenne's number theoretic transform.\nFor filtering a rather long input sequence xn() we can decomposed it into a number of short segments, each of which can be processed individually. The output yn()then becomes a combination of partial convolutions. The superposition principle for linear operators is used here.\nEach partial convolution can be solved using the Discrete Fourier Transform (DFT) implementing a fast FFT (Fast Fourier Transform) algorithm. This DFT approach is the most popular.\nIn this paper we use the Mersenne Number Transform (MNT) as an alternative for the DFT in the framework of a register transfer level (RTL) implementation of the filter operation. Even when the MNT does not have a fast algorithm it can be see that RTL in the natural level of abstraction for the implementation of the MNT.\nThis work is conceived as part of an academic exercise in the use of VHDL for modeling a DSP algorithm all the way from the mathematical specification to the circuit implementation.
Eje: Procesamiento distribuido y paralelo. Tratamiento de señales - Materia
-
Ciencias de la Computación
Fast Convolution
Mersenne Number Transform
Languages
Distributed
Parallel processing
RTL - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
.jpg)
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/4139
Ver los metadatos del registro completo
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RTL fast convolution using the mersenne number transformBria, Oscar N.Villagarcía Wanza, Horacio AlfredoCiencias de la ComputaciónFast ConvolutionMersenne Number TransformLanguagesDistributedParallel processingRTLVHDL is a versatile high level language for the specification and simulation of hardware components. Here a functional VHDL model is presented for performing fast convolution based on Mersenne's number theoretic transform.\nFor filtering a rather long input sequence xn() we can decomposed it into a number of short segments, each of which can be processed individually. The output yn()then becomes a combination of partial convolutions. The superposition principle for linear operators is used here.\nEach partial convolution can be solved using the Discrete Fourier Transform (DFT) implementing a fast FFT (Fast Fourier Transform) algorithm. This DFT approach is the most popular.\nIn this paper we use the Mersenne Number Transform (MNT) as an alternative for the DFT in the framework of a register transfer level (RTL) implementation of the filter operation. Even when the MNT does not have a fast algorithm it can be see that RTL in the natural level of abstraction for the implementation of the MNT.\nThis work is conceived as part of an academic exercise in the use of VHDL for modeling a DSP algorithm all the way from the mathematical specification to the circuit implementation.Eje: Procesamiento distribuido y paralelo. Tratamiento de señales1997info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/4139enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2026-09-24T11:33:41Zoai:digital.cic.gba.gob.ar:11746/4139Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412026-09-24 11:33:42.337CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
| dc.title.none.fl_str_mv |
RTL fast convolution using the mersenne number transform |
| title |
RTL fast convolution using the mersenne number transform |
| spellingShingle |
RTL fast convolution using the mersenne number transform Bria, Oscar N. Ciencias de la Computación Fast Convolution Mersenne Number Transform Languages Distributed Parallel processing RTL |
| title_short |
RTL fast convolution using the mersenne number transform |
| title_full |
RTL fast convolution using the mersenne number transform |
| title_fullStr |
RTL fast convolution using the mersenne number transform |
| title_full_unstemmed |
RTL fast convolution using the mersenne number transform |
| title_sort |
RTL fast convolution using the mersenne number transform |
| dc.creator.none.fl_str_mv |
Bria, Oscar N. Villagarcía Wanza, Horacio Alfredo |
| author |
Bria, Oscar N. |
| author_facet |
Bria, Oscar N. Villagarcía Wanza, Horacio Alfredo |
| author_role |
author |
| author2 |
Villagarcía Wanza, Horacio Alfredo |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ciencias de la Computación Fast Convolution Mersenne Number Transform Languages Distributed Parallel processing RTL |
| topic |
Ciencias de la Computación Fast Convolution Mersenne Number Transform Languages Distributed Parallel processing RTL |
| dc.description.none.fl_txt_mv |
VHDL is a versatile high level language for the specification and simulation of hardware components. Here a functional VHDL model is presented for performing fast convolution based on Mersenne's number theoretic transform.\nFor filtering a rather long input sequence xn() we can decomposed it into a number of short segments, each of which can be processed individually. The output yn()then becomes a combination of partial convolutions. The superposition principle for linear operators is used here.\nEach partial convolution can be solved using the Discrete Fourier Transform (DFT) implementing a fast FFT (Fast Fourier Transform) algorithm. This DFT approach is the most popular.\nIn this paper we use the Mersenne Number Transform (MNT) as an alternative for the DFT in the framework of a register transfer level (RTL) implementation of the filter operation. Even when the MNT does not have a fast algorithm it can be see that RTL in the natural level of abstraction for the implementation of the MNT.\nThis work is conceived as part of an academic exercise in the use of VHDL for modeling a DSP algorithm all the way from the mathematical specification to the circuit implementation. Eje: Procesamiento distribuido y paralelo. Tratamiento de señales |
| description |
VHDL is a versatile high level language for the specification and simulation of hardware components. Here a functional VHDL model is presented for performing fast convolution based on Mersenne's number theoretic transform.\nFor filtering a rather long input sequence xn() we can decomposed it into a number of short segments, each of which can be processed individually. The output yn()then becomes a combination of partial convolutions. The superposition principle for linear operators is used here.\nEach partial convolution can be solved using the Discrete Fourier Transform (DFT) implementing a fast FFT (Fast Fourier Transform) algorithm. This DFT approach is the most popular.\nIn this paper we use the Mersenne Number Transform (MNT) as an alternative for the DFT in the framework of a register transfer level (RTL) implementation of the filter operation. Even when the MNT does not have a fast algorithm it can be see that RTL in the natural level of abstraction for the implementation of the MNT.\nThis work is conceived as part of an academic exercise in the use of VHDL for modeling a DSP algorithm all the way from the mathematical specification to the circuit implementation. |
| publishDate |
1997 |
| dc.date.none.fl_str_mv |
1997 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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conferenceObject |
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publishedVersion |
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https://digital.cic.gba.gob.ar/handle/11746/4139 |
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https://digital.cic.gba.gob.ar/handle/11746/4139 |
| dc.language.none.fl_str_mv |
eng |
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eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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http://creativecommons.org/licenses/by/4.0/ |
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application/pdf |
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Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
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CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
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marisa.degiusti@sedici.unlp.edu.ar |
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