Arithmetic Coding for Data Compression
- PDF / 211,402 Bytes
- 4 Pages / 547.087 x 737.008 pts Page_size
- 2 Downloads / 248 Views
3. Cai, M., Deng, X.: Approximation and computation of arbitrage in frictional foreign exchange market. Electron. Notes Theor. Comput. Sci. 78, 1–10(2003) 4. Clinton, K.: Transactions costs and covered interest arbitrage: theory and evidence. J. Politcal Econ. 96(2), 358–370 (1988) 5. Deng, X., Li, Z.F., Wang, S.: Computational complexity of arbitrage in frictional security market. Int. J. Found. Comput. Sci. 13(5), 681–684 (2002) 6. Deng, X., Papadimitriou, C.: On the complexity of cooperative game solution concepts. Math. Oper. Res. 19(2), 257–266 (1994) 7. Deng, X., Papadimitriou, C., Safra, S.: On the complexity of price equilibria. J. Comput. System Sci. 67(2), 311–324 (2003) 8. Garey, M.R., Johnson, D.S.: Computers and intractability: a guide of the theory of NP-completeness. Freeman, San Francisco (1979) 9. Jones, C.K.: A network model for foreign exchange arbitrage, hedging and speculation. Int. J. Theor. Appl. Finance 4(6), 837– 852 (2001) 10. Lenstra Jr., H.W.: Integer programming with a fixed number of variables. Math. Oper. Res. 8(4), 538–548 (1983) 11. Mavrides, M.: Triangular arbitrage in the foreign exchange market – inefficiencies, technology and investment opportunities. Quorum Books, London (1992) 12. Megiddo, N.: Computational complexity and the game theory approach to cost allocation for a tree. Math. Oper. Res. 3, 189– 196 (1978) 13. Mundell, R.A.: Currency areas, exchange rate systems, and international monetary reform, paper delivered at Universidad del CEMA, Buenos Aires, Argentina. http://www. robertmundell.net/pdf/Currency (2000). Accessed 17 Apr 2000 14. Mundell, R.A.: Gold Would Serve into the 21st Century. Wall Street Journal, 30 September 1981, pp. 33 15. Zhang, S., Xu, C., Deng, X.: Dynamic arbitrage-free asset pricing with proportional transaction costs. Math. Finance 12(1), 89– 97 (2002)
Arithmetic Coding for Data Compression 1994; Howard, Vitter PAUL G. HOWARD1 , JEFFREY SCOTT VITTER2 1 Microway, Inc., Plymouth, MA, USA 2 Department of Computer Science, Purdue University, West Lafayette, IN, USA Keywords and Synonyms Entropy coding; Statistical data compression Problem Definition Often it is desirable to encode a sequence of data efficiently to minimize the number of bits required to transmit or store the sequence. The sequence may be a file or message consisting of symbols (or letters or characters) taken from a fixed input alphabet, but more generally the sequence
A
can be thought of as consisting of events, each taken from its own input set. Statistical data compression is concerned with encoding the data in a way that makes use of probability estimates of the events. Lossless compression has the property that the input sequence can be reconstructed exactly from the encoded sequence. Arithmetic coding is a nearly-optimal statistical coding technique that can produce a lossless encoding. Problem (Statistical data compression) INPUT: A sequence of m events a1 ; a2 ; : : : ; a m . The ith event ai is taken from a set of n distinct possible events e i;1 ; e i;2 ; : : : ; e i;n , with
Data Loading...
