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Título: FAST DECODING PREFIX CODES
Autor: LORENZA LEAO OLIVEIRA MORENO
Colaborador(es): RUY LUIZ MILIDIU - Orientador
Catalogação: 12/NOV/2003 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=4117&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=4117&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.4117
Resumo:
Even with the evolution of communication and storage devices, the use of complex data structures, like video and hypermedia documents, keeps increasing the demand for efficient data compression mechanisms. Prefix codes are one of the most known compressors, since they are executed by some compression methods that group different algorithms, besides presenting a good performance when used separately. A lot of approaches have been tried to improve the decoding speed of these codes. One major reason is that files are compressed and updated just a few times, whereas they have to be decompressed each time they are accessed. This work presents prefix codes and their decoding techniques in order to introduce a new coding scheme. In this scheme length-restricted codes are used to control the space requirements of the Look-up table, an efficient and fast prefix codes decoding method. Since restricted codewords are used, a small loss of compression efficiency is admitted. Empirical experiments indicate that this loss in the coded text is smaller than 11 percent if a character based model is used, and the observed average decoding speed is five times faster than the one for canonical codes. For a word based model, the average decoding speed is 3,5 times faster than a canonical decoder, but it decreases when a large number of symbols is used. Hence, this method is very suitable for applications where a character based model is used and extremely fast decoding is mandatory.
Descrição: Arquivo:   
COVER, ACKNOWLEDGEMENTS, RESUMO, ABSTRACT, SUMMARY AND LISTS PDF      
CHAPTER 1 PDF      
CHAPTER 2 PDF      
CHAPTER 3 PDF      
CHAPTER 4 PDF      
CHAPTER 5 PDF      
CHAPTER 6 PDF      
REFERENCES AND APPENDICES PDF