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International Conference on Manufacturing Automation 1992

作者： Leet, K.J. Kuniit, T.L. Noma, T. Department of Information Science Faculty of Science University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113 Japan Department of Artificial Intelligence Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka Fukuoka820 Japan

In this paper, we propose a syntactic pattern recognition method for non-schematic drawings, based on a new attributed graph grammar with flexible embedding. In our graph grammar, the embedding rule permits the nodes of a guest graph to be arbitrarily connected with the nodes of a host graph. The ambiguity caused by this flexible embedding is controlled with the evaluation of synthesized attributes and the check of context sensitivity. To integrate parsing with the synthesized attribute evaluation and the context sensitivity check, we also develop a bottom up parsing algorithm. © 1992 SPIE. All rights reserved.

关键词： Embeddings

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REDUCTIONS TO SETS OF LOW information-CONTENT 19th

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19TH INTERNATIONAL COLLOQUIUM ON AUTOMATA, LANGUAGES, AND PROGRAMMING ( ICALP 92 )

作者： ARVIND, V HAN, Y HEMACHANDRA, L KOBLER, J LOZANO, A MUNDHENK, M OGIWARA, M SCHONING, U SILVESTRI, R THIERAUF, T Department of Computer Science and Engineering Indian Institute of Technology New Delhi 110016 Delhi India Department of Computer Science University of Rochester Rochester 14627 NY United States Abteilung für Theoretische Informatik Universität Uhn Oberer Eselsberg Uhn D-W-7900 Germany Department of Software (L.S.I.) Universitat Politècnica de Catalunya Pau Gargallo 5 Barcelona E-08028 Spain Department of Computer Science and Information Mathematics University of Electro-Commmfications 1-5-1 Chofngaoka Chofu-si Tokyo 182 Japan Dipartimento Di Matematica Unlversits degli Studi di Roma La Sapienza Rome 00198 Italy

ISBN: (纸本)3540557199

In this paper we study the complexity of sets that reduce to sparse sets (and tally sets), and the complexity of the simplest sparse sets to which such sets reduce. We show even with respect to very flexible reductions that NP cannot have sparse hard sets unless P = NP;an immediate consequence of our results is: If any NP-complete set conjunctively reduces to a sparse set, then P = NP. We also show that any set A that reduces to some sparse set (via various types of reductions) in fact reduces by the same type of reduction to a sparse set that is simple relative to A. We give a complete characterization of the sets of low instance complexity in terms of reductions to tally sets;it follows that if P ≠ NP, then no set of low instance complexity can be complete for NP with respect to disjunctive reductions or conjunctive reductions. © Springer-Verlag Berlin Heidelberg 1992.

关键词： Artificial intelligence

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ON THE COMPLEXITY OF HYPERELLIPTIC DISCRETE LOGARITHM PROBLEM

ON THE COMPLEXITY OF HYPERELLIPTIC DISCRETE LOGARITHM PROBLE...

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WORKSHOP ON THE THEORY AND APPLICATION OF CRYPTOGRAPHIC TECHNIQUES

作者： SHIZUYA, H ITOH, T SAKURAI, K Department of Electrical Communications Faculity of Engineering Tohoku University Aramaki-Aza-Aoba Aoba-ku Sendai 980 Japan Département d’I.R.O. Université de Montréal C.P.6128 Succ.A Montréal H3C 3J7 QC Canada Department of Information Processing The Graduate School at Nagatsuta Tokyo Institute of Technology 4259 Nagatsuta Midori-ku Yokohama 227 Japan Computer & Information Systems Laboratory Mitsubishi Electric Corporation 5-1-1 Ofuna Kamakura 247 Japan

ISBN: (纸本)3540546200

We give a characterization for the intractability of hyperelliptic discrete logarithm problem from a viewpoint of computational complexity theory. It is shown that the language of which complexity is equivalent to that of the hyperelliptic discrete logarithm problem is in NP ∩ co-AM, and that especially for elliptic curves, the corresponding language is in NP ∩ co-NP. It should be noted here that the language of which complexity is equivalent to that of the discrete logarithm problem defined over the multiplicative group of a finite field is also characterized as in NP ∩ co-NP. © Springer-Verlag Berlin Heidelberg 1991.

关键词： Computational complexity

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An efficient retargetable microcode generator 19

An efficient retargetable microcode generator

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Proceedings of the 19th annual workshop on Microprogramming

作者： M. Balakrishnan P. C P Bhatt B. B. Madan Computing and Information Science Department University of GuelphGuelph OntarioCanadaN1G2W1 Department of Computer Science and Engineering Indian Institute of TechnologyDelhi New DelhiIndia110016

ISBN: (纸本)9780818607363

This paper presents a microcode generator, which accepts a source program (algorithm) and a target description (microarchitecture) as input and generates microcode to implement the algorithm on the defined microarchitecture. The target description is similar to the outputs produced by datapath synthesis phase in hardware design packages. Thus, it can be incorporated to synthesise a microprogrammed *** microcode generator is based on an algorithm which preserves retargetability without sacrificing on design time. This is achieved by implementing the generator in two phases: in the first phase, a set of 'feasible' register transfer operations (called base-set) is generated from the microarchitecture description. In the second phase, translation is carried out by simply searching and matching the source program statements with the base-set.

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Efficient Modulation for Band-Limited Channels

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IEEE Journal on Selected Areas in Communications 1984年第5期2卷 632-647页

作者： Forney, G. David Gallager, Robert G. Lang, Gordon R. Longstaff, Fred M. Qureshi, Shahid U. Motorola Information Systems Group Mansfield MA 02048 United States Department of Electrical Engineering Computer Science Massachusetts Institute of Technology Cambridge MA 02139 United States Motorola Information System Ltd. Rexdale Ont. M9V 1C1 Canada Codex Corporation Canton MA 02021 United States

This paper attempts to present a comprehensive tutorial survey of the development of efficient modulation techniques for bandlimited channels, such as telephone channels. After a historoyf advances in commercial high-speed modems and a discussion of theoretical limits, it reviews efforts to optimize two-dimensional signal constellations and presents further elaborations of uncoded modulation. Its principal emphasis, however, is on coded modulation twhniques, in which there is an explosion of current interest, both for research and for practical application. Both block-coded and trellis-coded modulation are covered, in a common framework. A few new techniques are presented. Copyright © 1984 by The Institute of Electrical and Electronics Engineers, Inc.

关键词： Modems Bandwidth Telephony Quadrature amplitude modulation Constellation diagram Modulation coding Signal to noise ratio History Explosions Layout

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Abstracts

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Environmental Management 1977年第1期1卷 67-96页

作者： Frankenfeld, John W. Schulz, Wolfgang McMurty, George J. Petersen, Gary W. May, G. A. Hering, F. S. Schwartz, J. I. Heywood, J. B. Chigier, N. A. Grohse, E. W. Walker, J. D. Colwell, R. R. Petrakis, L. Pergament, H. S. Thorpe, R. D. Schoepf, Richard W. Krzyczkowski, Roman Henneman, Suzanne S. Hudson, Charles L. Putnam, Evelyn S. Thiesen, Donna J. Parks, G. A. McCarty, Perry L. Leckie, J. O. Schrumpf, Barry J. Simonson, G. H. Paine, D. P. Lawrence, R. D. Pyott, W. T. Leh, M. Elders, W. Combs, J. Caplen, T. Harrison, F. L. Wong, K. M. Heft., R. E. Charnell, Robert L. Lehmann, Edward J. Mallon, Lawrence G. Hatfield, Cecile Adams, Gerald H. Johanning, James Talvitie, Antti Noll, Kenneth E. Miller, Terry Smiarowski, Joseph F. Willis, Cleve E. Foster, John H. Schlesinger, Benjamin Daetz, Douglas Lear, Donald U. Smith, Mona F. Hundemann, Audrey S. Crockett, Pernell W. Werner, Kirk G. Carroll, Thomas E. Maase, David L. Genco, Joseph E. Ifeadi, Christopher N. Lowman, F. G. Christensen, S. W. Van Winkle, W. Mattice, J. S. Harrison, Elizabeth A. Barker, James C. Chesness, Jerry L. Smith, Ralph E. Shaheeen, Donald G. Raney, R. Keith Borton, T. Wezernak, C. T. Raney, R. K. Sherwani, Jabbor K. Moreau, David H. Eisenberg, Norman A. Lynch, Cornelius J. Breeding, Roger J. Johnson, J. D. Foster, K. E. Mouat, D. A. Clark, R. Hyden, John William Owen, Wilfred Bayfield, Neil G. Barrow, Graham C. Stolz, Stephanie B. Wienckowski, Louis A. Brown, Betram S. Keyfitz, Nathan Wilson, W. L. Newman, Peter W. G. Bammi, Deepak Bammi, Dalip Goddard, James E. Chisholm, Tony Walsh, Cliff Brennan, Geoffrey Thompson, K. S. Richardson, R. Jensen, Clayton E. Brown, Dail W. Mirabito, John A. Cowing, Thomas G. Binghamton, Suny Siehl, George H. Albrecht, O. W. Alexander, Ariel Barde, Jean -Philippe Darby, William P. McMichael, Francis Clay Dunlap, Robert W. Muckleston, Keith W. Frankenhoff, Charles A. Giulini, Lorenzo T. Wyatt, T. Black, Peter E. Keating, William Thomas Leonard, M. E. Fisher, E. L. Brunelle, M. F. Dickinson, J. E. Pethig, Rudiger Clapham Exxon Research & Engineering Co. Linden Government Research Lab Coast Guard Washington D.C. Department of Transportation Washington D.C. Office For Remote Sensing of Earth Resources. NASA Earth Resources Survey Program Pennsylvania State University Washington D.C. Department of the Navy Washington D.C. Cambridge. Dept. of Mechanical Engineering Massachusetts Inst. of Technology USA Huntsville. School of Graduate Studies and Research Alabama Univ. USA Dept. of Microbiology. Office of Naval Research Maryland Univ. Arlington Research and Development Co. Pittsburgh AeroChem Research Labs. Inc. Princeton Dept. of the Interior Office of Library Services. Bibliographic Series (Final) Washington D.C. Interplan Corp. Santa Barbara Urban Mass Transportation Adm. Washington D.C. Naval Underwater Systems Center Newport Calif. Mercury Project. National Science Found Stanford Univ Washington D.C. Div. of Advanced Environmental Research & Tech. USA Corvallis. NASA Earth Resources Survey Program Oregon State Univ. Washington D.C. Riverside. Inst. of Geophysics and Planetary Physics National Science Foundation California Univ. Washington D.C. Livermore Lawrence Livermore Lab. California Univ. USA Atlantic Oceanographic and Meteorological Labs. National Oceanic and Atmospheric Administration Miami National Technical Information Service Springfield Miami Univ. Coral Gables School of Law National Oceanic and Atmospheric Administration Rockville National Academy of Sciences Office of Sea Grant Washington D. C. School of Law National Oceanic and Atmospheric Administration Office of Sea Grant. Rockville Norman. Dept. of Civil Engineering and Environmental Science. Urban Mass Transportation Administration Oklahoma Univ. Washington D. C. Knoxville.Dept. of Civil Engineering. Federal Highway Administration Tennessee Univ. Washington D. C. Amherst.Water Resources Research Center. Office of Water Research and Technology Massachusetts Univ. Washington D. C. Calif. Dept. of Industria

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Transactions on Rough Sets XII 1

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丛书名： Lecture Notes in computer Science

1000年

作者： James F. Peters Andrzej Skowron Roman Słowiński Pawan Lingras Duoqian Miao Shusaku Tsumoto

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Analysis and Interventions in Large Network Games

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Control, Robotics, and Autonomous Systems 1000年第1期4卷 455-486页

作者： Francesca Parise Asuman Ozdaglar 1Department of Electrical and Computer Engineering Cornell University Ithaca New York 14853 USA email: fp264@cornell.edu 2Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA email: asuman@mit.edu

We review classic results and recent progress on equilibrium analysis, dynamics, and optimal interventions in network games with both continuous and discrete strategy sets. We study strategic interactions in deterministic networks as well as networks generated from a stochastic network formation model. For the former case, we review a unifying framework for analysis based on the theory of variational inequalities. For the latter case, we highlight how knowledge of the stochastic network formation model can be used by a central planner to design interventions for large networks in a computationally efficient manner when exact network data are not available.

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The 3rd International Conference on Artificial Intelligence and computer Vision (AICV2023), March 5–7, 2023 1

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丛书名： Lecture Notes on Data engineering and Communications Technologies

1000年

作者： Aboul Ella Hassanien Abdelkrim Haqiq Ahmad Taher Azar KC Santosh M. A. Jabbar Adam Słowik Parthasarathy Subashini

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Computational Neuroscience: Mathematical and Statistical Perspectives

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Statistics and Its Application 1000年第1期5卷 183-214页

作者： Robert E. Kass Shun-Ichi Amari Kensuke Arai Emery N. Brown Casey O. Diekman Markus Diesmann Brent Doiron Uri T. Eden Adrienne L. Fairhall Grant M. Fiddyment Tomoki Fukai Sonja Grün Matthew T. Harrison Moritz Helias Hiroyuki Nakahara Jun-nosuke Teramae Peter J. Thomas Mark Reimers Jordan Rodu Horacio G. Rotstein Eric Shea-Brown Hideaki Shimazaki Shigeru Shinomoto Byron M. Yu Mark A. Kramer 1Department of Statistics Machine Learning Department and Center for the Neural Basis of Cognition Carnegie Mellon University Pittsburgh Pennsylvania 15213 USA email: kass@stat.cmu.edu 2Mathematical Neuroscience Laboratory RIKEN Brain Science Institute Wako Saitama Prefecture 351-0198 Japan 3Department of Mathematics and Statistics Boston University Boston Massachusetts 02215 USA 5Department of Anesthesia Harvard Medical School Boston Massachusetts 02115 USA 4Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA 6Department of Mathematical Sciences New Jersey Institute of Technology Newark New Jersey 07102 USA 8Department of Theoretical Systems Neurobiology Institute of Biology RWTH Aachen University 52062 Aachen Germany 7Institute of Neuroscience and Medicine Jülich Research Centre 52428 Jülich Germany 9Department of Mathematics University of Pittsburgh Pittsburgh Pennsylvania 15260 USA 10Department of Physiology and Biophysics University of Washington Seattle Washington 98105 USA 11Division of Applied Mathematics Brown University Providence Rhode Island 02912 USA 12Department of Integrated Theoretical Neuroscience Osaka University Suita Osaka Prefecture 565-0871 Japan 13Department of Mathematics Applied Mathematics and Statistics Case Western Reserve University Cleveland Ohio 44106 USA 14Department of Neuroscience Michigan State University East Lansing Michigan 48824 USA 15Department of Statistics University of Virginia Charlottesville Virginia 22904 USA 17Institute for Brain and Neuroscience Research New Jersey Institute of Technology Newark New Jersey 07102 USA 16Federated Department of Biological Sciences Rutgers University/New Jersey Institute of Technology Newark New Jersey 07102 USA 19Department of Physics Kyoto University Kyoto Kyoto Prefecture 606-8502 Japan 18Honda Research Institute Japan Wako Saitama Prefecture 351-0188 Japan 20Department of Electrical and Compute

Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field moves forward rapidly, new challenges are emerging. For maximal effectiveness, those working to advance computational neuroscience will need to appreciate and exploit the complementary strengths of mechanistic theory and the statistical paradigm.

关键词： neural data analysis neural modeling neural networks theoretical neuroscience

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