Open Problems in Communication and ComputationThomas M. Cover and B. Gopinatb The papers in this volume are the contributions to a special workshop on problems in communication and computation conducted in the summers of 1984 and 1985 in Morristown, New Jersey, and the summer of 1986 in Palo Alto. California. The structure of this workshop was unique: no recent results. no surveys. Instead. we asked for outstanding open prob~ lems in the field. There are many famous open problems, including the question P = NP?, the simplex conjecture in communication theory, the capacity region of the broadcast channel. and the two·helper problem in information theory. Beyond these well-defined problems are certain grand research goals. What is the general theory of information flow in stochastic networks? What is a comprehensive theory of computational complexity? What about a unification of algorithmic complexity and computational complex ity? Is there a notion of energy-free computation? And if so, where do information theory, communication theory, computer science, and physics meet at the atomic level? Is there a duality between computation and communication? Finally. what is the ultimate impact of algorithmic com plexity on probability theory? And what is its relationship to information theory? The idea was to present problems on the first day. try to solve them on the second day, and present the solutions on the third day. In actual fact, only one problem was solved during the meeting -- El Gamal's prob· lem on noisy communication over a common line. |
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Inhalt
1 | |
PROBLEMS IN COMMUNICATION | 27 |
PROBLEMS IN COMPUTATION | 102 |
PROBLEMS IN THE CRACKS it is is | 151 |
SOLUTIONS TO SIX OF THE PROBLEMS | 189 |
LIST OF CONTRIBUTORS | 223 |
Andere Ausgaben - Alle anzeigen
Open Problems in Communication and Computation Thomas M. Cover,B. Gopinath Keine Leseprobe verfügbar - 2011 |
Open Problems in Communication and Computation Thomas M Cover,B. Gopinath Keine Leseprobe verfügbar - 1987 |
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Ahlswede algorithm asymptotic AT&T Bell atoms Bayes binary trees bits Boolean functions bound Bruce Hajek Busy Beaver call attempt channel Computer Science conjecture constraints convergence Cover Departments covering radius Csiszár D(Po defined denote density Department of Electrical digit discrete logarithms Electrical Engineering Engineering and Statistics entropy equation expected number finite Finite Fields FRACTRAN program FRACTRAN-1 function f Gallager given graph Hajela IEEE Trans Inequality information theory input integer J.H. Conway Jacob Ziv Lemma linear code Mathematics matrix maximum measure minimum Murray Hill N.J.A. Sloane node optimal parity perfect hash perfect hash functions prob probability program-size complexity proof random variables result rotation distance satisfies sequence simplex simulate solution solved Stanford University Stanford started Statistics Stanford University stochastic stochastic process string subset Suppose test customer Theorem tion triangulations values vectors vertex zero