References

 

 

 

Home 
Preface 
Table of Contents 
References 
Purchase 
Authors 
News 
FAQ 
Contact 

[1] J. Abrahams. Code and parse trees for lossless source encoding. Proc.

Compression and Complexity of Sequences 1997, pages 145-171, 1998.

[2] N. Abramson. The ALOHA system¡Xanother alternative for computer communications.

AFIPS Conf. Proc., pages 281-285, 1970.

[3] N. M. Abramson. Information Theory and Coding. McGraw-Hill, New York,

1963.

[4] Y. S. Abu-Mostafa. Information theory. Complexity, pages 25-28, Nov.

1989.

[5] R. L. Adler, D. Coppersmith, and M. Hassner. Algorithms for sliding block

codes: an application of symbolic dynamics to information theory. IEEE

Trans. Inf. Theory, IT-29(1):5-22, 1983.

[6] R. Ahlswede. The capacity of a channel with arbitrary varying Gaussian

channel probability functions. Trans. 6th Prague Conf. Inf. Theory, pages

13-21, Sept. 1971.

[7] R. Ahlswede. Multi-way communication channels. In Proc. 2nd Int.

Symp. Inf. Theory (Tsahkadsor, Armenian S.S.R.), pages 23-52. Hungarian

Academy of Sciences, Budapest, 1971.

[8] R. Ahlswede. The capacity region of a channel with two senders and two

receivers. Ann. Prob., 2:805-814, 1974.

[9] R. Ahlswede. Elimination of correlation in random codes for arbitrarily

varying channels. Z. Wahrscheinlichkeitstheorie und verwandte Gebiete,

33:159-175, 1978.

[10] R. Ahlswede. Coloring hypergraphs: A new approach to multiuser source

coding. J. Comb. Inf. Syst. Sci., pages 220-268, 1979.

[11] R. Ahlswede. A method of coding and an application to arbitrarily varying

channels. J. Comb. Inf. Syst. Sci., pages 10-35, 1980.

[12] R. Ahlswede and T. S. Han. On source coding with side information via

a multiple access channel and related problems in multi-user information

theory. IEEE Trans. Inf. Theory, IT-29:396-412, 1983.

[13] R. Ahlswede and J. K¡Lorner. Source coding with side information and a

converse for the degraded broadcast channel. IEEE Trans. Inf. Theory,

IT-21:629-637, 1975.

[14] R. F. Ahlswede. Arbitrarily varying channels with states sequence known

to the sender. IEEE Trans. Inf. Theory, pages 621-629, Sept. 1986.

[15] R. F. Ahlswede. The maximal error capacity of arbitrarily varying channels

for constant list sizes (corresp.). IEEE Trans. Inf. Theory, pages 1416-1417,

July 1993.

[16] R. F. Ahlswede and G. Dueck. Identification in the presence of feedback: a

discovery of new capacity formulas. IEEE Trans. Inf. Theory, pages 30-36,

Jan. 1989.

[17] R. F. Ahlswede and G. Dueck. Identification via channels. IEEE Trans. Inf.

Theory, pages 15-29, Jan. 1989.

[18] R. F. Ahlswede, E. H. Yang, and Z. Zhang. Identification via compressed

data. IEEE Trans. Inf. Theory, pages 48-70, Jan. 1997.

[19] H. Akaike. Information theory and an extension of the maximum likelihood

principle. Proc. 2nd Int. Symp. Inf. Theory, pages 267-281, 1973.

[20] P. Algoet and T. M. Cover. A sandwich proof of the Shannon-

McMillan-Breiman theorem. Ann. Prob., 16(2):899-909, 1988.

[21] P. Algoet and T. M. Cover. Asymptotic optimality and asymptotic equipartition

property of log-optimal investment. Ann. Prob., 16(2):876-898, 1988.

[22] S. Amari. Differential-Geometrical Methods in Statistics. Springer-Verlag,

New York, 1985.

[23] S. I. Amari and H. Nagaoka. Methods of Information Geometry. Oxford

University Press, Oxford, 1999.

[24] V. Anantharam and S. Verdu. Bits through queues. IEEE Trans. Inf. Theory,

pages 4-18, Jan. 1996.

[25] S. Arimoto. An algorithm for calculating the capacity of an arbitrary discrete

memoryless channel. IEEE Trans. Inf. Theory, IT-18:14-20, 1972.

[26] S. Arimoto. On the converse to the coding theorem for discrete memoryless

channels. IEEE Trans. Inf. Theory, IT-19:357-359, 1973.

[27] R. B. Ash. Information Theory. Interscience, New York, 1965.

[28] J. Aczel and Z. Daroczy. On Measures of Information and Their Characterization.

Academic Press, New York, 1975.

[29] L. R. Bahl, J. Cocke, F. Jelinek, and J. Raviv. Optimal decoding of linear

codes for minimizing symbol error rate (corresp.). IEEE Trans. Inf. Theory,

pages 284-287, March 1974.

[30] A. Barron. Entropy and the central limit theorem. Ann. Prob., 14(1):

336-342, 1986.

[31] A. Barron and T. M. Cover. A bound on the financial value of information.

IEEE Trans. Inf. Theory, IT-34:1097-1100, 1988.

[32] A. Barron and T. M. Cover. Minimum complexity density estimation. IEEE

Trans. Inf. Theory, 37(4):1034-1054, July 1991.

[33] A. R. Barron. Logically smooth density estimation. Ph.D. thesis, Department

of Electrical Engineering, Stanford University, Stanford, CA, 1985.

[34] A. R. Barron. The strong ergodic theorem for densities: generalized Shannon

-McMillan-Breiman theorem. Ann. Prob., 13:1292-1303, 1985.

[35] A. R. Barron. Are Bayes rules consistent in information? Prob. Commun.

Computation, pages 85-91, 1987.

[36] A. R. Barron, J. Rissanen, and Bin Yu. The minimum description length principle

in coding and modeling. IEEE Trans. Inf. Theory, pages 2743-2760,

Oct. 1998.

[37] E. B. Baum. Neural net algorithms that learn in polynomial time from

examples and queries. IEEE Trans. Neural Networks, pages 5-19, 1991.

[38] W. Beckner. Inequalities in Fourier analysis. Ann. Math., 102:159-182,

1975.

[39] R. Bell and T. M. Cover. Competitive optimality of logarithmic investment.

Math. Oper. Res., 5(2):161-166, May 1980.

[40] R. Bell and T. M. Cover. Game-theoretic optimal portfolios. Manage. Sci.,

34(6):724-733, 1988.

[41] T. C. Bell, J. G. Cleary, and I. H. Witten. Text Compression. Prentice-Hall,

Englewood Cliffs, NJ, 1990.

[42] R. Bellman. Notes on matrix theory. IV: An inequality due to Bergstrom.

Am. Math. Monthly, 62:172-173, 1955.

[43] C. H. Bennett and G. Brassard. Quantum cryptography: public key distribution

and coin tossing. Proc. IEEE Int. Conf. Comput., pages 175-179,

1984.

[44] C. H. Bennett, D. P. DiVincenzo, J. Smolin, and W. K. Wootters. Mixed

state entanglement and quantum error correction. Phys. Rev. A, pages

3824-3851, 1996.

[45] C. H. Bennett, D. P. DiVincenzo, and J. A. Smolin. Capacities of quantum

erasure channels. Phys. Rev. Lett., pages 3217-3220, 1997.

[46] C. H. Bennett and S. J. Wiesner. Communication via one- and two-particle

operators on Einstein-podolsky-Rosen states. Phys. Rev. Lett., pages

2881-2884, 1992.

[47] C. H. Bennett. Demons, engines and the second law. Sci. Am.,

259(5):108-116, Nov. 1987.

[48] C. H. Bennett and R. Landauer. The fundamental physical limits of computation.

Sci. Am., 255(1):48-56, July 1985.

[49] C. H. Bennett and P. W. Shor. Quantum information theory. IEEE Trans.

Inf. Theory, IT-44:2724-2742, Oct. 1998.

[50] J. Bentley, D. Sleator, R. Tarjan, and V. Wei. Locally adaptive data

compression scheme. Commun. ACM, pages 320-330, 1986.

[51] R. Benzel. The capacity region of a class of discrete additive degraded

interference channels. IEEE Trans. Inf. Theory, IT-25:228-231, 1979.

[52] T. Berger. Rate Distortion Theory: A Mathematical Basis for Data

Compression. Prentice-Hall, Englewood Cliffs, NJ, 1971.

[53] T. Berger. Multiterminal source coding. In G. Longo (Ed.), The Information

Theory Approach to Communications. Springer-Verlag, New York, 1977.

[54] T. Berger and R. W. Yeung. Multiterminal source encoding with one distortion

criterion. IEEE Trans. Inf. Theory, IT-35:228-236, 1989.

[55] P. Bergmans. Random coding theorem for broadcast channels with degraded

components. IEEE Trans. Inf. Theory, IT-19:197-207, 1973.

[56] E. R. Berlekamp. Block Coding with Noiseless Feedback. Ph.D. thesis, MIT,

Cambridge, MA, 1964.

[57] C. Berrou, A. Glavieux, and P. Thitimajshima. Near Shannon limit errorcorrecting

coding and decoding: Turbo codes. Proc. 1993 Int. Conf. Commun.,

pages 1064-1070, May 1993.

[58] D. Bertsekas and R. Gallager. Data Networks, 2nd ed.. Prentice-Hall, Englewood

Cliffs, NJ, 1992.

[59] M. Bierbaum and H. M. Wallmeier. A note on the capacity region of the

multiple access channel. IEEE Trans. Inf. Theory, IT-25:484, 1979.

[60] E. Biglieri, J. Proakis, and S. Shamai. Fading channels: information-theoretic

and communications aspects. IEEE Trans. Inf. Theory, pages 2619-2692,

October 1998.

[61] N. Blachman. The convolution inequality for entropy powers. IEEE Trans.

Inf. Theory, IT-11:267-271, Apr. 1965.

[62] D. Blackwell, L. Breiman, and A. J. Thomasian. Proof of Shannons transmission

theorem for finite-state indecomposable channels. Ann. Math. Stat.,

pages 1209-1220, 1958.

[63] D. Blackwell, L. Breiman, and A. J. Thomasian. The capacity of a class of

channels. Ann. Math. Stat., 30:1229-1241, 1959.

[64] D. Blackwell, L. Breiman, and A. J. Thomasian. The capacities of certain

channel classes under random coding. Ann. Math. Stat., 31:558-567,

1960.

[65] R. Blahut. Computation of channel capacity and rate distortion functions.

IEEE Trans. Inf. Theory, IT-18:460-473, 1972.

[66] R. E. Blahut. Information bounds of the Fano-Kullback type. IEEE Trans.

Inf. Theory, IT-22:410-421, 1976.

[67] R. E. Blahut. Principles and Practice of Information Theory. Addison-

Wesley, Reading, MA, 1987.

[68] R. E. Blahut. Hypothesis testing and information theory. IEEE Trans. Inf.

Theory, IT-20:405-417, 1974.

[69] R. E. Blahut. Theory and Practice of Error Control Codes. Addison-Wesley,

Reading, MA, 1983.

[70] B. M. Hochwald, G. Caire, B. Hassibi, and T. L. Marzetta (Eds.). IEEE

Trans. Inf. Theory, Special Issue on Space-Time Transmission, Reception,

Coding and Signal-Processing, Vol. 49, Oct. 2003.

[71] L. Boltzmann. Beziehung Zwischen dem zweiten Hauptsatze der

mechanischen W¡Larmertheorie und der Wahrscheilichkeitsrechnung respektive

den Saetzen uber das W¡Larmegleichgwicht. Wien. Ber., pages 373-435,

1877.

[72] R. C. Bose and D. K. Ray-Chaudhuri. On a class of error correcting binary

group codes. Inf. Control, 3:68-79, Mar. 1960.

[73] H. J. Brascamp and E. J. Lieb. Best constants in Young's inequality, its

converse and its generalization to more than three functions. Adv. Math.,

20:151-173, 1976.

[74] L. Breiman. The individual ergodic theorems of information theory. Ann.

Math. Stat., 28:809-811, 1957. With correction made in 31:809-810.

[75] L. Breiman. Optimal gambling systems for favourable games. In Fourth

Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1,

pages 65-78. University of California Press, Berkeley, CA, 1961.

[76] L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone. Classification

and Regression Trees. Wadsworth & Brooks, Pacific Grove, CA, 1984.

[77] L. Brillouin. Science and Information Theory. Academic Press, New York,

1962.

[78] J. A. Bucklew. The source coding theorem via Sanov's theorem. IEEE

Trans. Inf. Theory, pages 907-909, Nov. 1987.

[79] J. A. Bucklew. Large Deviation Techniques in Decision, Simulation, and

Estimation. Wiley, New York, 1990.

[80] J. P. Burg. Maximum entropy spectral analysis. Ph.D. thesis, Department of

Geophysics, Stanford University, Stanford, CA, 1975.

[81] M. Burrows and D. J. Wheeler. A Block-Sorting Lossless Data Compression

Algorithm (Tech. Rept. 124). Digital Systems Research Center, Palo Alto,

CA, May 1994.

[82] A. R. Calderbank. The art of signaling: fifty years of coding theory. IEEE

Trans. Inf. Theory, pages 2561-2595, Oct. 1998.

[83] A. R. Calderbank and P. W. Shor. Good quantum error-correcting codes

exist. Phys. Rev. A, pages 1098-1106, 1995.

[84] A. Carleial. Outer bounds on the capacity of the interference channel. IEEE

Trans. Inf. Theory, IT-29:602-606, 1983.

[85] A. B. Carleial. A case where interference does not reduce capacity. IEEE

Trans. Inf. Theory, IT-21:569-570, 1975.

[86] G. Chaitin. Information-Theoretic Incompleteness. World Scientific, Singapore,

1992.

[87] G. J. Chaitin. On the length of programs for computing binary sequences.

J. ACM, pages 547-569, 1966.

[88] G. J. Chaitin. The limits of mathematics. J. Universal Comput. Sci.,

2(5):270-305, 1996.

[89] G. J. Chaitin. On the length of programs for computing binary sequences.

J. ACM, 13:547-569, 1966.

[90] G. J. Chaitin. Information theoretical limitations of formal systems. J. ACM,

21:403-424, 1974.

[91] G. J. Chaitin. Randomness and mathematical proof. Sci. Am., 232(5):47-52,

May 1975.

[92] G. J. Chaitin. Algorithmic information theory. IBM J. Res. Dev., 21:350-359,

1977.

[93] G. J. Chaitin. Algorithmic Information Theory. Cambridge University Press,

Cambridge, 1987.

[94] C. S. Chang and J. A. Thomas. Huffman algebras for independent random

variables. Discrete Event Dynam. Syst., 4:23-40, 1994.

[95] C. S. Chang and J. A. Thomas. Effective bandwidth in high speed digital

networks. IEEE J. Select. Areas Commun., 13:1091-1114, Aug. 1995.

[96] R. Chellappa. Markov Random Fields: Theory and Applications. Academic

Press, San Diego, CA, 1993.

[97] H. Chernoff. A measure of the asymptotic efficiency of tests of a hypothesis

based on a sum of observations. Ann. Math. Stat., 23:493-507,

1952.

[98] B. S. Choi and T. M. Cover. An information-theoretic proof of Burg's

maximum entropy spectrum. Proc. IEEE, 72:1094-1095, 1984.

[99] N. Chomsky. Three models for the description of language. IEEE Trans.

Inf. Theory, pages 113-124, Sept. 1956.

[100] P. A. Chou, M. Effros, and R. M. Gray. A vector quantization approach to

universal noiseless coding and quantization. IEEE Trans. Inf. Theory, pages

1109-1138, July 1996.

[101] K. L. Chung. A note on the ergodic theorem of information theory. Ann.

Math. Stat., 32:612-614, 1961.

[102] B. S. Clarke and A. R. Barron. Information-theoretic asymptotics of Bayes'

methods. IEEE Trans. Inf. Theory, pages 453-471, May 1990.

[103] B. S. Clarke and A. R. Barron. Jeffreys' prior is asymptotically least favorable

under entropy risk. J. Stat. Planning Inf., pages 37-60, Aug. 1994.

[104] M. Costa and T. M. Cover. On the similarity of the entropy power inequality

and the Brunn-Minkowski inequality. IEEE Trans. Inf. Theory, IT-

30:837-839, 1984.

[105] M. H. M. Costa. On the Gaussian interference channel. IEEE Trans. Inf.

Theory, pages 607-615, Sept. 1985.

[106] M. H. M. Costa and A. A. El Gamal. The capacity region of the discrete

memoryless interference channel with strong interference. IEEE Trans. Inf.

Theory, pages 710-711, Sept. 1987.

[107] T. M. Cover. Geometrical and statistical properties of systems of linear

inequalities with applications to pattern recognition. IEEE Trans. Electron.

Computation, pages 326-334, 1965.

[108] T. M. Cover. Universal Gambling Schemes and the Complexity Measures of

Kolmogorov and Chaitin (Tech. Rept. 12). Department of Statistics, Stanford

University, Stanford, CA, Oct. 1974.

[109] T. M. Cover. Open problems in information theory. Proc. Moscow Inf.

Theory Workshop, pages 35-36, 1975.

[110] T. M. Cover. Universal portfolios. Math. Finance, pages 1-29, Jan. 1991.

[111] T. M. Cover. Comments on broadcast channels. IEEE Trans. Inf. Theory,

pages 2524-2530, Oct. 1998.

[112] T. M. Cover. Shannon and investment. IEEE Inf. Theory Newslett (Special

Golden Jubilee Issue), pp. 10-11, June 1998.

[113] T. M. Cover and M. S. Chiang. Duality between channel capacity and

rate distortion with two-sided state information. IEEE Trans. Inf. Theory,

IT-48(6):1629-1638, June 2002.

[114] T. M. Cover, P. G'acs, and R. M. Gray. Kolmogorov's contributions to information

theory and algorithmic complexity. Ann. Prob., pages 840-865, July

1989.

[115] T. M. Cover, A. A. El Gamal, and M. Salehi. Multiple access channels with

arbitrarily correlated sources. IEEE Trans. Inf. Theory, pages 648-657, Nov.

1980.

[116] T. M. Cover and P. E. Hart. Nearest neighbor pattern classification. IEEE

Trans. Inf. Theory, pages 21-27, Jan. 1967.

[117] T. M. Cover and S. Pombra. Gaussian feedback capacity. IEEE Trans. Inf.

Theory, pages 37-43, January 1989.

[118] T. M. Cover and J. A. Thomas. Determinant inequalities via information

theory. SIAM J. Matrix Anal. and Its Applications, 9(3):384-392, July 1988.

[119] T. M. Cover. Broadcast channels. IEEE Trans. Inf. Theory, IT-18:2-14,

1972.

[120] T. M. Cover. Enumerative source encoding. IEEE Trans. Inf. Theory, IT-

19(1):73-77, Jan. 1973.

[121] T. M. Cover. An achievable rate region for the broadcast channel. IEEE

Trans. Inf. Theory, IT-21:399-404, 1975.

[122] T. M. Cover. A proof of the data compression theorem of Slepian and Wolf

for ergodic sources. IEEE Trans. Inf. Theory, IT-22:226-228, 1975.

[123] T. M. Cover. An algorithm for maximizing expected log investment return.

IEEE Trans. Inf. Theory, IT-30(2):369-373, 1984.

[124] T. M. Cover. Kolmogorov complexity, data compression and inference.

In J. Skwirzynski (Ed.), The Impact of Processing Techniques on Communications,

Vol. 91 of Applied Sciences. Martinus-Nijhoff, Dordrecht, The

Netherlands, 1985.

[125] T. M. Cover. On the competitive optimality of Huffman codes. IEEE Trans.

Inf. Theory, 37(1):172-174, Jan. 1991.

[126] T. M. Cover. Universal portfolios. Math. Finance, pages 1-29, Jan. 1991.

[127] T. M. Cover and A El Gamal. Capacity theorems for the relay channel.

IEEE Trans. Inf. Theory, IT-25:572-584, 1979.

[128] T. M. Cover and A. El Gamal. An information theoretic proof of Hadamard's

inequality. IEEE Trans. Inf. Theory, IT-29(6):930-931, Nov. 1983.

[129] T. M. Cover, A. El Gamal, and M. Salehi. Multiple access channels with

arbitrarily correlated sources. IEEE Trans. Inf. Theory, IT-26:648-657,

1980.

[130] T. M. Cover. Pick the largest number, Open Problems in Communication

and Computation. Ed. by T. M. Cover and B. Gopinath, page 152, New

York, 1987.

[131] T. M. Cover and R. King. A convergent gambling estimate of the entropy

of English. IEEE Trans. Inf. Theory, IT-24:413-421, 1978.

[132] T. M. Cover and C. S. K. Leung. Some equivalences between Shannon

entropy and Kolmogorov complexity. IEEE Trans. Inf. Theory, IT-

24:331-338, 1978.

[133] T. M. Cover and C. S. K. Leung. An achievable rate region for the multiple

access channel with feedback. IEEE Trans. Inf. Theory, IT-27:292-298,

1981.

[134] T. M. Cover, R. J. McEliece, and E. Posner. Asynchronous multiple access

channel capacity. IEEE Trans. Inf. Theory, IT-27:409-413, 1981.

[135] T. M. Cover and E. Ordentlich. Universal portfolios with side information.

IEEE Trans. Inf. Theory, IT-42:348-363, Mar. 1996.

[136] T. M. Cover and S. Pombra. Gaussian feedback capacity. IEEE Trans. Inf.

Theory, IT-35:37-43, 1989.

[137] H. Cramer. Mathematical Methods of Statistics. Princeton University Press,

Princeton, NJ, 1946.

[138] I. Csisz'ar. Information type measures of difference of probability distributions

and indirect observations. Stud. Sci. Math. Hung., 2:299-318,

1967.

[139] I Csisz'ar. On the computation of rate distortion functions. IEEE Trans. Inf.

Theory, IT-20:122-124, 1974.

[140] I. Csisz'ar. I-divergence geometry of probability distributions and minimization

problems. Ann. Prob., pages 146-158, Feb. 1975.

[141] I Csisz'ar. Sanov property, generalized I-projection and a conditional limit

theorem. Ann. Prob., 12:768-793, 1984.

[142] I. Csisz'ar. Information theory and ergodic theory. Probl. Contr. Inf. Theory,

pages 3-27, 1987.

[143] I. Csisz'ar. A geometric interpretation of Darroch and Ratcliff's generalized

iterative scaling. Ann. Stat., pages 1409-1413, 1989.

[144] I. Csisz'ar. Why least squares and maximum entropy? An axiomatic approach

to inference for linear inverse problems. Ann. Stat., pages 2032-2066, Dec.

1991.

[145] I. Csisz'ar. Arbitrarily varying channels with general alphabets and states.

IEEE Trans. Inf. Theory, pages 1725-1742, Nov. 1992.

[146] I. Csisz'ar. The method of types. IEEE Trans. Inf. Theory, pages 2505-2523,

October 1998.

[147] I. Csisz'ar, T. M. Cover, and B. S. Choi. Conditional limit theorems under

Markov conditioning. IEEE Trans. Inf. Theory, IT-33:788-801, 1987.

[148] I. Csisz'ar and J. K¡Lorner. Towards a general theory of source networks. IEEE

Trans. Inf. Theory, IT-26:155-165, 1980.

[149] I. Csisz'ar and J. K¡Lorner. Information Theory: Coding Theorems for Discrete

Memoryless Systems. Academic Press, New York, 1981.

[150] I. Csisz'ar and J. K¡Lorner. Feedback does not affect the reliability function of

a DMC at rates above capacity (corresp.). IEEE Trans. Inf. Theory, pages

92-93, Jan. 1982.

[151] I. Csisz'ar and J. K¡Lorner. Broadcast channels with confidential messages.

IEEE Trans. Inf. Theory, pages 339-348, May 1978.

[152] I. Csisz'ar and J. K¡Lorner. Graph decomposition: a new key to coding

theorems. IEEE Trans. Inf. Theory, pages 5-12, Jan. 1981.

[153] I. Csisz'ar and G. Longo. On the Error Exponent for Source Coding and

for Testing Simple Statistical Hypotheses. Hungarian Academy of Sciences,

Budapest, 1971.

[154] I. Csisz'ar and P. Narayan. Capacity of the Gaussian arbitrarily varying channel.

IEEE Trans. Inf. Theory, pages 18-26, Jan. 1991.

[155] I. Csisz'ar and G. Tusn'ady. Information geometry and alternating minimization

procedures. Statistics and Decisions, Supplement Issue 1:205-237,

1984.

[156] G. B. Dantzig and D. R. Fulkerson. On the max-flow min-cut theorem of

networks. In H. W. Kuhn and A. W. Tucker (Eds.), Linear Inequalities and

Related Systems (Vol. 38 of Annals of Mathematics Study), pages 215-221.

Princeton University Press, Princeton, NJ, 1956.

[157] J. N. Darroch and D. Ratcliff. Generalized iterative scaling for log-linear

models. Ann. Math. Stat., pages 1470-1480, 1972.

[158] I. Daubechies. Ten Lectures on Wavelets. SIAM, Philadelphia, 1992.

[159] L. D. Davisson. Universal noiseless coding. IEEE Trans. Inf. Theory, IT-

19:783-795, 1973.

[160] L. D. Davisson. Minimax noiseless universal coding for Markov sources.

IEEE Trans. Inf. Theory, pages 211-215, Mar. 1983.

[161] L. D. Davisson, R. J. McEliece, M. B. Pursley, and M. S. Wallace. Efficient

universal noiseless source codes. IEEE Trans. Inf. Theory, pages 269-279,

May 1981.

[162] A. Dembo. Information Inequalities and Uncertainty Principles (Technical

Report), Department of Statistics, Stanford University, Stanford, CA,

1990.

[163] A. Dembo. Information inequalities and concentration of measure. Ann.

Prob., pages 927-939, 1997.

[164] A. Dembo, T. M. Cover, and J. A. Thomas. Information theoretic inequalities.

IEEE Trans. Inf. Theory, 37(6):1501-1518, Nov. 1991.

[165] A. Dembo and O. Zeitouni. Large Deviations Techniques and Applications.

Jones & Bartlett, Boston, 1993.

[166] A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from

incomplete data via the EM algorithm. J. Roy. Stat. Soc. B, 39(1):1-38,

1977.

[167] L. Devroye and L. Gyorfi. Nonparametric Density Estimation: The L1 View.

Wiley, New York, 1985.

[168] L. Devroye, L. Gyorfi, and G. Lugosi. A Probabilistic Theory of Pattern

Recognition. Springer-Verlag, New York, 1996.

[169] D. P. DiVincenzo, P. W. Shor, and J. A. Smolin. Quantum-channel capacity

of very noisy channels. Phys. Rev. A, pages 830-839, 1998.

[170] R.L. Dobrushin. General formulation of Shannon's main theorem of information

theory. Usp. Math. Nauk, 14:3-104, 1959. Translated in Am. Math.

Soc. Trans., 33:323-438.

[171] R. L. Dobrushin. Survey of Soviet research in information theory. IEEE

Trans. Inf. Theory, pages 703-724, Nov. 1972.

[172] D. L. Donoho. De-noising by soft-thresholding. IEEE Trans. Inf. Theory,

pages 613-627, May 1995.

[173] R. O. Duda and P. E. Hart. Pattern Classification and Scene Analysis. Wiley,

New York, 1973.

[174] G. Dueck. Maximal error capacity regions are smaller than average error

capacity regions for multi-user channels. Probl. Contr. Inf. Theory, pages

11-19, 1978.

[175] G. Dueck. The capacity region of the two-way channel can exceed the inner

bound. Inf. Control, 40:258-266, 1979.

[176] G. Dueck. Partial feedback for two-way and broadcast channels. Inf. Control,

46:1-15, 1980.

[177] G. Dueck and J. K¡Lorner. Reliability function of a discrete memoryless channel

at rates above capacity. IEEE Trans. Inf. Theory, IT-25:82-85, 1979.

[178] P. M. Ebert. The capacity of the Gaussian channel with feedback. Bell Syst.

Tech. J., 49:1705-1712, Oct. 1970.

[179] P. M. Ebert. The capacity of the Gaussian channel with feedback. Bell Syst.

Tech. J., pages 1705-1712, Oct. 1970.

[180] K. Eckschlager. Information Theory in Analytical Chemistry. Wiley, New

York, 1994.

[181] M. Effros, K. Visweswariah, S. R. Kulkarni, and S. Verdu. Universal lossless

source coding with the Burrows-Wheeler transform. IEEE Trans. Inf.

Theory, IT-48:1061-1081, May 2002.

[182] B. Efron and R. Tibshirani. An Introduction to the Bootstrap. Chapman &

Hall, London, 1993.

[183] H. G. Eggleston. Convexity (Cambridge Tracts in Mathematics and Mathematical

Physics, No. 47). Cambridge University Press, Cambridge, 1969.

[184] A. El Gamal. The feedback capacity of degraded broadcast channels. IEEE

Trans. Inf. Theory, IT-24:379-381, 1978.

[185] A. El Gamal. The capacity region of a class of broadcast channels. IEEE

Trans. Inf. Theory, IT-25:166-169, 1979.

[186] A. El Gamal and T. M. Cover. Multiple user information theory. Proc.

IEEE, 68:1466-1483, 1980.

[187] A. El Gamal and T. M. Cover. Achievable rates for multiple descriptions.

IEEE Trans. Inf. Theory, IT-28:851-857, 1982.

[188] A. El Gamal and E. C. Van der Meulen. A proof of Marton's coding theorem

for the discrete memoryless broadcast channel. IEEE Trans. Inf. Theory,

IT-27:120-122, 1981.

[189] P. Elias. Error-free coding. IRE Trans. Inf. Theory, IT-4:29-37, 1954.

[190] P. Elias. Coding for noisy channels. IRE Conv. Rec., Pt. 4, pages 37-46,

1955.

[191] P. Elias. Networks of Gaussian channels with applications to feedback systems.

IEEE Trans. Inf. Theory, pages 493-501, July 1967.

[192] P. Elias. The efficient construction of an unbiased random sequence. Ann.

Math. Stat., pages 865-870, 1972.

[193] P. Elias. Universal codeword sets and representations of the integers. IEEE

Trans. Inf. Theory, pages 194-203, Mar. 1975.

[194] P. Elias. Interval and recency rank source coding: two on-line adaptive

variable-length schemes. IEEE Trans. Inf. Theory, pages 3-10, Jan. 1987.

[195] P. Elias, A. Feinstein, and C. E. Shannon. A note on the maximum flow

through a network. IEEE Trans. Inf. Theory, pages 117-119, December

1956.

[196] R. S. Ellis. Entropy, Large Deviations, and Statistical Mechanics. Springer-

Verlag, New York, 1985.

[197] A. Ephremides and B. Hajek. Information theory and communication

networks: an unconsummated union. IEEE Trans. Inf. Theory, pages

2416-2434, Oct. 1998.

[198] W. H. R. Equitz and T. M. Cover. Successive refinement of information.

IEEE Trans. Inf. Theory, pages 269-275, Mar. 1991.

[199] Ky Fan. On a theorem of Weyl concerning the eigenvalues of linear transformations

II. Proc. Nat. Acad. Sci. USA, 36:31-35, 1950.

[200] Ky Fan. Some inequalities concerning positive-definite matrices. Proc. Cambridge

Philos. Soc., 51:414-421, 1955.

[201] R. M. Fano. Class notes for Transmission of Information, course 6.574

(Technical Report). MIT, Cambridge, MA, 1952.

[202] R. M. Fano. Transmission of Information: A Statistical Theory of Communication.

Wiley, New York, 1961.

[203] M. Feder. A note on the competetive optimality of Huffman codes. IEEE

Trans. Inf. Theory, 38(2):436-439, Mar. 1992.

[204] M. Feder, N. Merhav, and M. Gutman. Universal prediction of individual

sequences. IEEE Trans. Inf. Theory, pages 1258-1270, July 1992.

[205] A. Feinstein. A new basic theorem of information theory. IRE Trans. Inf.

Theory, IT-4:2-22, 1954.

[206] A. Feinstein. Foundations of Information Theory. McGraw-Hill, New York,

1958.

[207] A. Feinstein. On the coding theorem and its converse for finite-memory

channels. Inf. Control, 2:25-44, 1959.

[208] W. Feller. An Introduction to Probability Theory and Its Applications, 2nd

ed., Vol. 1. Wiley, New York, 1957.

[209] R. A. Fisher. On the mathematical foundations of theoretical statistics. Philos.

Trans. Roy. Soc., London A, 222:309-368, 1922.

[210] R. A. Fisher. Theory of statistical estimation. Proc. Cambridge Philos. Soc.,

22:700-725, 1925.

[211] B. M. Fitingof. Optimal encoding with unknown and variable message statistics.

Probl. Inf. Transm. (USSR), pages 3-11, 1966.

[212] B. M. Fitingof. The compression of discrete information. Probl. Inf. Transm.

(USSR), pages 28-36, 1967.

[213] L. R. Ford and D. R. Fulkerson. Maximal flow through a network. Can. J.

Math., pages 399-404, 1956.

[214] L. R. Ford and D. R. Fulkerson. Flows in Networks. Princeton University

Press, Princeton, NJ, 1962.

[215] G. D. Forney. Exponential error bounds for erasure, list and decision feedback

schemes. IEEE Trans. Inf. Theory, IT-14:549-557, 1968.

[216] G. D. Forney. Information Theory: unpublished course notes. Stanford

University, Stanford, CA, 1972.

[217] G. J. Foschini. Layered space-time architecture for wireless communication

in a fading environment when using multi-element antennas. Bell Syst. Tech.

J., 1(2):41-59, 1996.

[218] P. Franaszek, P. Tsoucas, and J. Thomas. Context allocation for multiple dictionary

data compression. In Proc. IEEE Int. Symp. Inf. Theory, Trondheim,

Norway, page 12, 1994.

[219] P. A. Franaszek. On synchronous variable length coding for discrete noiseless

channels. Inf. Control, 15:155-164, 1969.

[220] T. Gaarder and J. K. Wolf. The capacity region of a multiple-access discrete

memoryless channel can increase with feedback. IEEE Trans. Inf. Theory,

IT-21:100-102, 1975.

[221] D. Gabor. Theory of communication. J. Inst. Elec. Engg., pages 429-457,

Sept. 1946.

[222] P. Gacs and J. K¡Lorner. Common information is much less than mutual information.

Probl. Contr. Inf. Theory, pages 149-162, 1973.

[223] R. G. Gallager. Source coding with side information and universal coding.

Unpublished manuscript, also presented at the Int. Symp. Inf. Theory, Oct.

1974.

[224] R. G. Gallager. A simple derivation of the coding theorem and some applications.

IEEE Trans. Inf. Theory, IT-11:3-18, 1965.

[225] R. G. Gallager. Capacity and coding for degraded broadcast channels. Probl.

Peredachi Inf., 10(3):3-14, 1974.

[226] R. G. Gallager. Basic limits on protocol information in data communication

networks. IEEE Trans. Inf. Theory, pages 385-398, July

1976.

[227] R. G. Gallager. A minimum delay routing algorithm using distributed computation.

IEEE Trans. Commun., pages 73-85, Jan. 1977.

[228] R. G. Gallager. Variations on a theme by Huffman. IEEE Trans. Inf. Theory,

pages 668-674, Nov. 1978.

[229] R. G. Gallager. Source Coding with Side Information and Universal Coding

(Tech. Rept. LIDS-P-937). Laboratory for Information Decision Systems,

MIT, Cambridge, MA, 1979.

[230] R. G. Gallager. A perspective on multiaccess channels. IEEE Trans. Inf.

Theory, pages 124-142, Mar. 1985.

[231] R. G. Gallager. Low density parity check codes. IRE Trans. Inf. Theory,

IT-8:21-28, Jan. 1962.

[232] R. G. Gallager. Low Density Parity Check Codes. MIT Press, Cambridge,

MA, 1963.

[233] R. G. Gallager. Information Theory and Reliable Communication. Wiley,

New York, 1968.

[234] A. A. El Gamal and T. M. Cover. Achievable rates for multiple descriptions.

IEEE Trans. Inf. Theory, pages 851-857, November 1982.

[235] A. El Gamal. Broadcast channels with and without feedback. 11th Ann.

Asilomar Conf. Circuits, pages 180-183, Nov. 1977.

[236] A. El Gamal. Capacity of the product and sum of two unmatched broadcast

channels. Probl. Peredachi Inf., pages 3-23, Jan.-Mar. 1980.

[237] A. A. El Gamal. The feedback capacity of degraded broadcast channels

(corresp.). IEEE Trans. Inf. Theory, pages 379-381, May 1978.

[238] A. A. El Gamal. The capacity of a class of broadcast channels. IEEE Trans.

Inf. Theory, pages 166-169, Mar. 1979.

[239] A. A. El Gamal. The capacity of the physically degraded Gaussian broadcast

channel with feedback (corresp.). IEEE Trans. Inf. Theory, pages 508-511,

July 1981.

[240] A. A. El Gamal and E. C. van der Meulen. A proof of Marton's coding

theorem for the discrete memoryless broadcast channel. IEEE Trans. Inf.

Theory, pages 120-122, Jan. 1981.

[241] I. M. Gelfand, A. N. Kolmogorov, and A. M. Yaglom. On the general

definition of mutual information. Rept. Acad. Sci. USSR, pages 745-748,

1956.

[242] S. I. Gelfand. Capacity of one broadcast channel. Probl. Peredachi Inf.,

pages 106-108, July-Sept. 1977.

[243] S. I. Gelfand and M. S. Pinsker. Capacity of a broadcast channel with one

deterministic component. Probl. Peredachi Inf., pages 24-34, Jan.-Mar.

1980.

[244] S. I. Gelfand and M. S. Pinsker. Coding for channel with random parameters.

Probl. Contr. Inf. Theory, pages 19-31, 1980.

[245] A. Gersho and R. M. Gray. Vector Quantization and Signal Compression.

Kluwer, Boston, 1992.

[246] G. G. Rayleigh and J. M. Cioffi. Spatio-temporal coding for wireless communication.

IEEE Trans. Commun., 46:357-366, 1998.

[247] J. D. Gibson and J. L. Melsa. Introduction to Nonparametric Detection with

Applications. IEEE Press, New York, 1996.

[248] E. N. Gilbert. Codes based on inaccurate source probabilities. IEEE Trans.

Inf. Theory, pages 304-314, May 1971.

[249] E. N. Gilbert and E. F. Moore. Variable length binary encodings. Bell Syst.

Tech. J., 38:933-967, 1959.

[250] S. Goldman. Some fundamental considerations concerning noise reduction

and range in radar and communication. Proc. Inst. Elec. Engg., pages

584-594, 1948.

[251] S. Goldman. Information Theory. Prentice-Hall, Englewood Cliffs, NJ,

1953.

[252] A. Goldsmith and M. Effros. The capacity region of Gaussian broadcast

channels with intersymbol interference and colored Gaussian noise. IEEE

Trans. Inf. Theory, 47:2-8, Jan. 2001.

[253] S. W. Golomb. Run-length encodings. IEEE Trans. Inf. Theory, pages

399-401, July 1966.

[254] S. W. Golomb, R. E. Peile, and R. A. Scholtz. Basic Concepts in Information

Theory and Coding: The Adventures of Secret Agent 00111 (Applications of

Communications Theory). Plenum Publishing, New York, 1994.

[255] A. J. Grant, B. Rimoldi, R. L. Urbanke, and P. A. Whiting. Rate-splitting

multiple access for discrete memoryless channels. IEEE Trans. Inf. Theory,

pages 873-890, Mar. 2001.

[256] R. M. Gray. Source Coding Theory. Kluwer, Boston, 1990.

[257] R. M. Gray and L. D. Davisson, (Eds.). Ergodic and Information Theory.

Dowden, Hutchinson & Ross, Stroudsburg, PA, 1977.

[258] R. M. Gray and Lee D. Davisson. Source coding theorems without the

ergodic assumption. IEEE Trans. Inf. Theory, pages 502-516, July 1974.

[259] R. M. Gray. Sliding block source coding. IEEE Trans. Inf. Theory, IT-

21:357-368, 1975.

[260] R. M. Gray. Entropy and Information Theory. Springer-Verlag, New York,

1990.

[261] R. M. Gray and A. Wyner. Source coding for a simple network. Bell Syst.

Tech. J., 58:1681-1721, 1974.

[262] U. Grenander and G. Szego. Toeplitz Forms and Their Applications. University

of California Press, Berkeley, CA, 1958.

[263] B. Gr¡Lunbaum. Convex Polytopes. Interscience, New York, 1967.

[264] S. Guiasu. Information Theory with Applications. McGraw-Hill, New York,

1976.

[265] B. E. Hajek and M. B. Pursley. Evaluation of an achievable rate region for

the broadcast channel. IEEE Trans. Inf. Theory, pages 36-46, Jan. 1979.

[266] R. V. Hamming. Error detecting and error correcting codes. Bell Syst. Tech.

J., 29:147-160, 1950.

[267] T. S. Han. The capacity region for the deterministic broadcast channel with

a common message (corresp.). IEEE Trans. Inf. Theory, pages 122-125,

Jan. 1981.

[268] T. S. Han and S. I. Amari. Statistical inference under multiterminal data

compression. IEEE Trans. Inf. Theory, pages 2300-2324, Oct. 1998.

[269] T. S. Han and S. Verdu. New results in the theory of identification via

channels. IEEE Trans. Inf. Theory, pages 14-25, Jan. 1992.

[270] T. S. Han. Nonnegative entropy measures of multivariate symmetric correlations.

Inf. Control, 36(2):133-156, 1978.

[271] T. S. Han. The capacity region of a general multiple access channel with

certain correlated sources. Inf. Control, 40:37-60, 1979.

[272] T. S. Han. Information-Spectrum Methods in Information Theory. Springer-

Verlag, New York, 2002.

[273] T. S. Han and M. H. M. Costa. Broadcast channels with arbitrarily correlated

sources. IEEE Trans. Inf. Theory, IT-33:641-650, 1987.

[274] T. S. Han and K. Kobayashi. A new achievable rate region for the interference

channel. IEEE Trans. Inf. Theory, IT-27:49-60, 1981.

[275] R. V. Hartley. Transmission of information. Bell Syst. Tech. J., 7:535, 1928.

[276] C. W. Helstrom. Elements of Signal Detection and Estimation. Prentice-Hall,

Englewood Cliffs, NJ, 1995.

[277] Y. Hershkovits and J. Ziv. On sliding-window universal data compression

with limited memory. IEEE Trans. Inf. Theory, pages 66-78, Jan. 1998.

[278] P. A. Hocquenghem. Codes correcteurs d'erreurs. Chiffres, 2:147-156,

1959.

[279] J. L. Holsinger. Digital Communication over Fixed Time-Continuous

Channels with Memory, with Special Application to Telephone Channels

(Technical Report). MIT, Cambridge, MA, 1964.

[280] M. L. Honig, U. Madhow, and S. Verdu. Blind adaptive multiuser detection.

IEEE Trans. Inf. Theory, pages 944-960, July 1995.

[281] J. E. Hopcroft and J. D. Ullman. Introduction to Automata Theory, Formal

Languages and Computation. Addison-Wesley, Reading, MA, 1979.

[282] Y. Horibe. An improved bound for weight-balanced tree. Inf. Control,

34:148-151, 1977.

[283] D. A. Huffman. A method for the construction of minimum redundancy

codes. Proc. IRE, 40:1098-1101, 1952.

[284] J. Y. Hui. Switching an Traffic Theory for Integrated Broadband Networks.

Kluwer, Boston, 1990.

[285] J. Y. N. Hui and P. A. Humblet. The capacity region of the totally asynchronous

multiple-access channel. IEEE Trans. Inf. Theory, pages 207-216,

Mar. 1985.

[286] S. Ihara. On the capacity of channels with additive non-Gaussian noise. Inf.

Contr., pages 34-39, 1978.

[287] S. Ihara. Information Theory for Continuous Systems. World Scientific, Singapore,

1993.

[288] K. A. Schouhamer Immink, Paul H. Siegel, and Jack K. Wolf. Codes

for digital recorders. IEEE Trans. Inf. Theory, pages 2260-2299, Oct.

1998.

[289] N. S. Jayant (Ed.). Waveform Quantization and Coding. IEEE Press, New

York, 1976.

[290] N. S. Jayant and P. Noll. Digital Coding of Waveforms. Prentice-Hall, Englewood

Cliffs, NJ, 1984.

[291] E. T. Jaynes. Information theory and statistical mechanics. Phys. Rev.,

106:620, 1957.

[292] E. T. Jaynes. Information theory and statistical mechanics II. Phys. Rev.,

108:171, 1957.

[293] E. T. Jaynes. On the rationale of maximum entropy methods. Proc. IEEE,

70:939-952, 1982.

[294] E. T. Jaynes. Papers on Probability, Statistics and Statistical Physics. Reidel,

Dordrecht, The Netherlands, 1982.

[295] F. Jelinek. Buffer overflow in variable length encoding of fixed rate sources.

IEEE Trans. Inf. Theory, IT-14:490-501, 1968.

[296] F. Jelinek. Evaluation of expurgated error bounds. IEEE Trans. Inf. Theory,

IT-14:501-505, 1968.

[297] F. Jelinek. Probabilistic Information Theory. McGraw-Hill, New York,

1968.

[298] F. Jelinek. Statistical Methods for Speech Recognition. MIT Press, Cambridge,

MA, 1998.

[299] R Jozsa and B. Schumacher. A new proof of the quantum noiseless coding

theorem. J Mod. Opt., pages 2343-2350, 1994.

[300] G. G. Langdon, Jr. A note on the Ziv-Lempel model for compressing

individual sequences. IEEE Trans. Inf. Theory, pages 284-287, Mar. 1983.

[301] J. Justesen. A class of constructive asymptotically good algebraic codes.

IEEE Trans. Inf. Theory, IT-18:652-656, 1972.

[302] M. Kac. On the notion of recurrence in discrete stochastic processes. Bull.

Am. Math. Soc., pages 1002-1010, Oct. 1947.

[303] T. Kailath and J. P. M. Schwalkwijk. A coding scheme for additive noise

channels with feedback. Part I: No bandwidth constraints. IEEE Trans. Inf.

Theory, IT-12:172-182, 1966.

[304] T. Kailath and H. V. Poor. Detection of stochastic processes. IEEE Trans.

Inf. Theory, pages 2230-2259, Oct. 1998.

[305] S. Karlin. Mathematical Methods and Theory in Games, Programming and

Economics, Vol. 2. Addison-Wesley, Reading, MA, 1959.

[306] J. Karush. A simple proof of an inequality of McMillan. IRE Trans. Inf.

Theory, IT-7:118, 1961.

[307] F. P. Kelly. Notes on effective bandwidth. Stochastic Networks Theory and

Applications, pages 141-168, 1996.

[308] J. Kelly. A new interpretation of information rate. Bell Syst. Tech. J,

35:917-926, July 1956.

[309] J. H. B. Kemperman. On the Optimum Rate of Transmitting Information

(Lecture Notes in Mathematics), pages 126-169. Springer Verlag, New York,

1967.

[310] M. Kendall and A. Stuart. The Advanced Theory of Statistics. Macmillan,

New York, 1977.

[311] A. Y. Khinchin. Mathematical Foundations of Information Theory. Dover,

New York, 1957.

[312] J. C. Kieffer. A simple proof of the Moy-Perez generalization of the Shannon

-McMillan theorem. Pacific J. Math., 51:203-206, 1974.

[313] J. C. Kieffer. A survey of the theory of source coding with a fidelity criterion.

IEEE Trans. Inf. Theory, pages 1473-1490, Sept. 1993.

[314] Y. H. Kim. Feedback capacity of first-order moving average Gaussian channel.

Proc. IEEE Int. Symp. Information Theory, Adelaide, pages 416-420,

Sept. 2005.

[315] D. E. Knuth. Dynamic Huffman coding. J. Algorithms, pages 163-180,

1985.

[316] D. E. Knuth. Art of Computer Programming.

[317] D. E. Knuth and A. C. Yao. The complexity of random number generation.

In J. F. Traub (Ed.), Algorithms and Complexity: Recent Results and New

Directions (Proceedings of the Symposium on New Directions and Recent

Results in Algorithms and Complexity, Carnegie-Mellon University, 1976),

pages 357-428. Academic Press, New York, 1976.

[318] A. N. Kolmogorov. A new metric invariant of transitive dynamical systems

and automorphism in Lebesgue spaces. Dokl. Akad. Nauk SSSR, pages

861-864, 1958.

[319] A. N. Kolmogorov. On the Shannon theory of information transmission in

the case of continuous signals. IRE Trans. Inf. Theory, IT-2:102-108, Sept.

1956.

[320] A. N. Kolmogorov. A new invariant for transitive dynamical systems. Dokl.

Acad. Nauks SSR, 119:861-864, 1958.

[321] A. N. Kolmogorov. Three approaches to the quantitative definition of

information. Probl. Inf. Transm. (USSR), 1:4-7, 1965.

[322] A. N. Kolmogorov. Logical basis for information theory and probability

theory. IEEE Trans. Inf. Theory, IT-14:662-664, 1968.

[323] A. N. Kolmogorov. The theory of transmission of information. In Selected

Works of A. N. Kolmogorov, Vol. III: Information Theory and the Theory of

Algorithms, Session on scientific problems of automatization in industry,

Vol. 1, Plenary talks, Izd. Akad. Nauk SSSR, Moscow, 1957, pages 66-99.

Kluwer, Dordrecht, The Netherlands, 1993.

[324] J. K¡Lorner and K. Marton. The comparison of two noisy channels. In

I. Csisz'ar and P. Elias (Ed.), Topics in Information Theory (Coll. Math. Soc.

J. Bolyai, No. 16), pages 411-423. North-Holland, Amsterdam, 1977.

[325] J. K¡Lorner and K. Marton. General broadcast channels with degraded message

sets. IEEE Trans. Inf. Theory, IT-23:60-64, 1977.

[326] J. K¡Lorner and K. Marton. How to encode the modulo 2 sum of two binary

sources. IEEE Trans. Inf. Theory, IT-25:219-221, 1979.

[327] J. K¡Lorner and A. Orlitsky. Zero error information theory. IEEE Trans. Inf.

Theory, IT-44:2207-2229, Oct. 1998.

[328] V. A. Kotel'nikov. On the transmission capacity of ¡§ether¡¨ and wire in

electrocommunications. Izd. Red. Upr. Svyazi RKKA, 44, 1933.

[329] V. A. Kotel'nikov. The Theory of Optimum Noise Immunity. McGraw-Hill,

New York, 1959.

[330] L. G. Kraft. A device for quantizing, grouping and coding amplitude modulated

pulses. Master's thesis, Department of Electrical Engineering, MIT,

Cambridge, MA, 1949.

[331] R. E. Krichevsky. Laplace's law of succession and universal encoding. IEEE

Trans. Inf. Theory, pages 296-303, Jan. 1998.

[332] R. E. Krichevsky. Universal Compression and Retrieval. Kluwer, Dordrecht,

The Netherlands, 1994.

[333] R. E. Krichevsky and V. K. Trofimov. The performance of universal encoding.

IEEE Trans. Inf. Theory, pages 199-207, Mar. 1981.

[334] S. R. Kulkarni, G. Lugosi, and S. S. Venkatesh. Learning pattern classification:

a survey. IEEE Trans. Inf. Theory, pages 2178-2206, Oct. 1998.

[335] S. Kullback. Information Theory and Statistics. Wiley, New York, 1959.

[336] S. Kullback. A lower bound for discrimination in terms of variation. IEEE

Trans. Inf. Theory, IT-13:126-127, 1967.

[337] S. Kullback, J. C. Keegel, and J. H. Kullback. Topics in Statistical Information

Theory. Springer-Verlag, Berlin, 1987.

[338] S. Kullback and M. A. Khairat. A note on minimum discrimination information.

Ann. Math. Stat., pages 279-280, 1966.

[339] S. Kullback and R. A. Leibler. On information and sufficiency. Ann. Math.

Stat., 22:79-86, 1951.

[340] H. J. Landau and H. O. Pollak. Prolate spheroidal wave functions, Fourier

analysis and uncertainty: Part II. Bell Syst. Tech. J., 40:65-84, 1961.

[341] H. J. Landau and H. O. Pollak. Prolate spheroidal wave functions, Fourier

analysis and uncertainty: Part III. Bell Syst. Tech. J., 41:1295-1336, 1962.

[342] G. G. Langdon. An introduction to arithmetic coding. IBM J. Res. Dev.,

28:135-149, 1984.

[343] G. G. Langdon and J. J. Rissanen. A simple general binary source code.

IEEE Trans. Inf. Theory, IT-28:800, 1982.

[344] A. Lapidoth and P. Narayan. Reliable communication under channel uncertainty.

IEEE Trans. Inf. Theory, pages 2148-2177, Oct. 1998.

[345] A. Lapidoth and J. Ziv. On the universality of the LZ-based decoding algorithm.

IEEE Trans. Inf. Theory, pages 1746-1755, Sept. 1998.

[346] H. A. Latan'e. Criteria for choice among risky ventures. J. Polit. Econ.,

38:145-155, Apr. 1959.

[347] H. A. Latan'e

and D.L. Tuttle. Criteria for portfolio building. J. Finance,

22:359-373, Sept. 1967.

[348] E. A. Lee and D. G. Messerschmitt. Digital Communication, 2nd ed.

Kluwer, Boston, 1994.

[349] J. Leech and N. J. A. Sloane. Sphere packing and error-correcting codes.

Can. J. Math, pages 718-745, 1971.

[350] E. L. Lehmann and H. Scheff'e. Completeness, similar regions and unbiased

estimation. Sankhya, 10:305-340, 1950.

[351] A. Lempel and J. Ziv. On the complexity of finite sequences. IEEE Trans.

Inf. Theory, pages 75-81, Jan. 1976.

[352] L. A. Levin. On the notion of a random sequence. Sov. Math. Dokl.,

14:1413-1416, 1973.

[353] L. A. Levin and A. K. Zvonkin. The complexity of finite objects and the

development of the concepts of information and randomness by means of

the theory of algorithms. Russ. Math. Surv., 25/6:83-124, 1970.

[354] M. Li and P. Vitanyi. An Introduction to Kolmogorov Complexity and Its

Applications, 2nd ed. Springer-Verlag, New York, 1997.

[355] H. Liao. Multiple access channels. Ph.D. thesis, Department of Electrical

Engineering, University of Hawaii, Honolulu, 1972.

[356] S. Lin and D. J. Costello, Jr. Error Control Coding: Fundamentals and

Applications. Prentice-Hall, Englewood Cliffs, NJ, 1983.

[357] D. Lind and B. Marcus. Symbolic Dynamics and Coding. Cambridge

University Press, Cambridge, 1995.

[358] Y. Linde, A. Buzo, and R. M. Gray. An algorithm for vector quantizer

design. IEEE Trans. Commun., COM-28:84-95, 1980.

[359] T. Linder, G. Lugosi, and K. Zeger. Rates of convergence in the source

coding theorem in empirical quantizer design. IEEE Trans. Inf. Theory,

pages 1728-1740, Nov. 1994.

[360] T. Linder, G. Lugosi, and K. Zeger. Fixed-rate universal lossy source coding

and rates of convergence for memoryless sources. IEEE Trans. Inf. Theory,

pages 665-676, May 1995.

[361] D. Lindley. Boltzmann's Atom: The Great Debate That Launched A Revolution

in Physics. Free Press, New York, 2001.

[362] A. Liversidge. Profile of Claude Shannon. In N. J. A. Sloane and A. D.

Wyner (Eds.), Claude Elwood Shannon Collected Papers. IEEE Press, Piscataway,

NJ, 1993 (Omni magazine, Aug. 1987.)

[363] S. P. Lloyd. Least Squares Quantization in PCM (Technical Report). Bell

Lab. Tech. Note, 1957.

[364] G. Louchard and Wojciech Szpankowski. On the average redundancy

rate of the Lempel-Ziv code. IEEE Trans. Inf. Theory, pages 2-8, Jan.

1997.

[365] L. Lovasz. On the Shannon capacity of a graph. IEEE Trans. Inf. Theory,

IT-25:1-7, 1979.

[366] R. W. Lucky. Silicon Dreams: Information, Man and Machine. St. Martin's

Press, New York, 1989.

[367] D. J. C. Mackay. Information Theory, Inference, and Learning Algorithms.

Cambridge University Press, Cambridge, 2003.

[368] D. J. C. MacKay and R. M. Neal. Near Shannon limit performance of

low-density parity-check codes. Electron. Lett., pages 1645-1646, Mar.

1997.

[369] F. J. MacWilliams and N. J. A. Sloane. The Theory of Error-Correcting

Codes. North-Holland, Amsterdam, 1977.

[370] B. Marcus. Sofic systems and encoding data. IEEE Trans. Inf. Theory,

IT-31(3):366-377, May 1985.

[371] R. J. Marks. Introduction to Shannon Sampling and Interpolation Theory.

Springer-Verlag New York, 1991.

[372] A. Marshall and I. Olkin. Inequalities: Theory of Majorization and Its Applications.

Academic Press, New York, 1979.

[373] A. Marshall and I. Olkin. A convexity proof of Hadamard's inequality. Am.

Math. Monthly, 89(9):687-688, 1982.

[374] P. Martin-L¡Lof. The definition of random sequences. Inf. Control, 9:602-619,

1966.

[375] K. Marton. Information and information stability of ergodic sources. Probl.

Inf. Transm. (VSSR), pages 179-183, 1972.

[376] K. Marton. Error exponent for source coding with a fidelity criterion. IEEE

Trans. Inf. Theory, IT-20:197-199, 1974.

[377] K. Marton. A coding theorem for the discrete memoryless broadcast channel.

IEEE Trans. Inf. Theory, IT-25:306-311, 1979.

[378] J. L. Massey and P. Mathys. The collision channel without feedback. IEEE

Trans. Inf. Theory, pages 192-204, Mar. 1985.

[379] R. A. McDonald. Information rates of Gaussian signals under criteria constraining

the error spectrum. D. Eng. dissertation, Yale University School

of Electrical Engineering, New Haven, CT, 1961.

[380] R. A. McDonald and P. M. Schultheiss. Information rates of Gaussian

signals under criteria constraining the error spectrum. Proc. IEEE, pages

415-416, 1964.

[381] R. A. McDonald and P. M. Schultheiss. Information rates of Gaussian signals

under criteria constraining the error spectrum. Proc. IEEE, 52:415-416,

1964.

[382] R. J. McEliece, D. J. C. MacKay, and J. F. Cheng. Turbo decoding as an

instance of Pearl's belief propagation a