Abstract
This paper presents a new generalized particle model (GPM) to generate the prediction coding for lossless data compression. Local rules for particle movement in GPM, parallel algorithm and its implementation structure to generate the desired predictive coding are discussed. The proposed GPM approach has advantages in terms of encoding speed, parallelism, scalability, simplicity, and easy hardware implementation over other sequential lossless compression methods.
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Shuai, D. (2008). Parallel Lossless Data Compression: A Particle Dynamic Approach. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_34
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DOI: https://doi.org/10.1007/978-3-540-87442-3_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87440-9
Online ISBN: 978-3-540-87442-3
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