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Data Compression Using Adaptive Coding and Partial String Matching
Open accessAbstract
The recently developed technique of arithmetic coding, in conjunction with a Markov model of the source, is a powerful method of data compression in situations where a linear treatment is inappropriate. Adaptive coding allows the model to be constructed dynamically by both encoder and decoder during the course of the transmission, and has been shown to incur a smaller coding overhead than explicit transmission of the model's statistics. But there is a basic conflict between the desire to use high-order Markov models and the need to have them formed quickly as the initial part of the message is sent. This paper describes how the conflict can be resolved with partial string matching, and reports experimental results which show that mixed-case English text can be coded in as little as 2.2 bits/ character with no prior knowledge of the source.
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Cited by
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Hilbert, M., & López, P. (2011) · Science · doi:10.1126/science.1200970 · Cited by 1,643
Data Compression Using Dynamic Markov Modelling
Cormack, G. V., & Horspool, R. N. S. (1987) · The Computer Journal · doi:10.1093/comjnl/30.6.541 · Cited by 213
LeZi-Update: An Information-Theoretic Framework for Personal Mobility Tracking in PCS Networks
Bhattacharya, A., & Das, S. K. (2002) · Wireless Networks · doi:10.1023/a:1013759724438 · Cited by 205
A Note on Brain Actuated Spelling with the Berlin Brain-Computer Interface
Blankertz, B., Krauledat, M., Dornhege, G., Williamson, J., Murray-Smith, R., & Müller, K.-R. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-73281-5_83 · Cited by 106
Metadata
- Authors
- Cleary, J., & Witten, I.
- Venue
- IEEE Transactions on Communications
- Published
- 1984
- Volume
- 32
- Issue
- 4
- Pages
- 396-402
- ISSN
- 0090-6778 (ISSN-L)
- OpenAlex
- W2161628678
- Cited by
- 1,241
- References
- 0
- FWCI
- 4.14
- Type
- journal article
- Language
- en
- Open access
- green
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