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13
The Viterbi algorithm
 Proceedings of the IEEE
, 1973
"... vol. 6, no. 8, pp. 211220, 1951. [7] J. L. Anderson and J. W..Ryon, “Electromagnetic radiation in accelerated systems, ” Phys. Rev., vol. 181, pp. 17651775, 1969. [8] C. V. Heer, “Resonant frequencies of an electromagnetic cavity in an accelerated system of reference, ” Phys. Reu., vol. 134, pp. A ..."
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Cited by 985 (3 self)
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vol. 6, no. 8, pp. 211220, 1951. [7] J. L. Anderson and J. W..Ryon, “Electromagnetic radiation in accelerated systems, ” Phys. Rev., vol. 181, pp. 17651775, 1969. [8] C. V. Heer, “Resonant frequencies of an electromagnetic cavity in an accelerated system of reference, ” Phys. Reu., vol. 134, pp. A799A804, 1964. [9] T. C. Mo, “Theory of electrodynamics in media in noninertial frames and applications, ” J. Math. Phys., vol. 11, pp. 25892610, 1970.
Auction algorithms for network flow problems: A tutorial introduction
 Comput. Optim. Appl
, 1992
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On the History of Combinatorial Optimization (till 1960)
"... As a coherent mathematical discipline, combinatorial optimization is relatively young. When studying the history of the field, one observes a number of independent lines of research, separately considering problems like optimum assignment, shortest spanning tree, transportation, and the traveling ..."
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Cited by 14 (0 self)
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As a coherent mathematical discipline, combinatorial optimization is relatively young. When studying the history of the field, one observes a number of independent lines of research, separately considering problems like optimum assignment, shortest spanning tree, transportation, and the traveling salesman problem. Only in the 1950's, when the unifying tool of linear and integer programming became available and the area of operations research got intensive attention, these problems were put into one framework, and relations between them were laid. Indeed, linear programming forms the hinge in the history of combinatorial optimization. Its initial conception by Kantorovich and Koopmans was motivated by combinatorial applications, in particular in transportation and transshipment. After the formulation of linear programming as generic problem, and the development in 1947 by Dantzig of the simplex method as a tool, one has tried to attack about all combinatorial opti
Nondecreasing paths in weighted graphs, or: how to optimally read a train schedule
 In Proc. SODA
, 2008
"... A travel booking office has timetables giving arrival and departure times for all scheduled trains, including their origins and destinations. A customer presents a starting city and demands a route with perhaps several train connections taking him to his destination as early as possible. The booking ..."
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Cited by 6 (2 self)
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A travel booking office has timetables giving arrival and departure times for all scheduled trains, including their origins and destinations. A customer presents a starting city and demands a route with perhaps several train connections taking him to his destination as early as possible. The booking office must find the best route for its customers. This problem was first considered in the theory of algorithms by George Minty [Min58], who reduced it to a problem on directed weighted graphs: find a path from a given source to a given target such that the consecutive weights on the path are nondecreasing and the last weight on the path is minimized. Minty gave the first algorithm for the single source version of the problem, in which one finds minimum last weight nondecreasing paths from the source to every other vertex. In this paper we give the first linear time algorithm for this problem. We also define an all pairs version for the problem and give a strongly polynomial truly subcubic algorithm for it. 1
Efficient Algorithms for Path Problems in Weighted Graphs
, 2008
"... Problems related to computing optimal paths have been abundant in computer science since its emergence as a field. Yet for a large number of such problems we still do not know whether the stateoftheart algorithms are the best possible. A notable example of this phenomenon is the all pairs shorte ..."
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Cited by 5 (0 self)
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Problems related to computing optimal paths have been abundant in computer science since its emergence as a field. Yet for a large number of such problems we still do not know whether the stateoftheart algorithms are the best possible. A notable example of this phenomenon is the all pairs shortest paths problem in a directed graph with real edge weights. The best algorithm (modulo small polylogarithmic improvements) for this problem runs in cubic time, a running time known since the 1960s (by Floyd and Warshall). Our grasp of many such fundamental algorithmic questions is far from optimal, and the major goal of this thesis is to bring some new insights into efficiently solving path problems in graphs. We focus on several path problems optimizing different measures: shortest paths, maximum bottleneck paths, minimum nondecreasing paths, and various extensions. For the allpairs versions of these path problems we use an algebraic approach. We obtain improved algorithms using reductions
Routing Reconfiguration in IP Networks
, 2000
"... This thesis will focus on new methods for efficient IP routing reconfiguration in the presence of topological changes. A fast response to changing network conditions is essential to prevent network routing instability as well as to ensure quality of service parameters. We will identify problems with ..."
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Cited by 2 (0 self)
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This thesis will focus on new methods for efficient IP routing reconfiguration in the presence of topological changes. A fast response to changing network conditions is essential to prevent network routing instability as well as to ensure quality of service parameters. We will identify problems with the current degree of adaptiveness of existing IP routing schemes. New algorithms and protocols will be presented to improve such adaptiveness at different time scales. The first problem is about the recomputation of shortest path trees performed in linkstate protocols. This recomputation is generally done by static SPT algorithms. This means that all the previous information on the previous SPT is deleted and needs to be recomputed from scratch. We develop many new and different dynamic shortest path algorithms to perform this recomputation in an efficient way. By using information from the previous tree, these new dynamic algorithms can achieve great savings in computational complexity. Furthermore...
Development and Testing of Dynamic Traffic Assignment . . .
, 1994
"... This report describes the methodologies and procedures developed through a contract to the University of Texas at Austin, in collaboration with the University of Maryland, to address these essential needs. Specifically, a simulationassignment methodology has been developed to describe user's ..."
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This report describes the methodologies and procedures developed through a contract to the University of Texas at Austin, in collaboration with the University of Maryland, to address these essential needs. Specifically, a simulationassignment methodology has been developed to describe user's path choices in the network in response to realtime information, and the resulting flow patterns that propagate through the network, yielding information about overall quality of service and effectiveness, as well as localized information pointing to problem spots and opportunities for improvement. This methodology is intended for use offline for evaluation purposes, or online for prediction purpose in support of advanced traffic management functions. In additional, algorithmic procedures have been developed to determine the best paths to which users should be directed so as to optimize overall system performance. Powerful extension
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"... In 1967, Andrew Viterbi first presented his now famous algorithm for thedecoding of convolutional codes [1][3]. A few years later, what is nowknown as the Viterbi decoding algorithm (VDA) was applied to the detection of data signals distorted by intersymbol interference (ISI) [4][8]. For such app ..."
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In 1967, Andrew Viterbi first presented his now famous algorithm for thedecoding of convolutional codes [1][3]. A few years later, what is nowknown as the Viterbi decoding algorithm (VDA) was applied to the detection of data signals distorted by intersymbol interference (ISI) [4][8]. For such applications, the algorithm is often referred to as a Viterbi equalizer (VE). This tutorial focuses on the latter application, because it provides insight into how the VDA (or the VE), which is a maximumlikelihood sequence estimator (MLSE), actually works. The VDA has become very popular for processing ISIdistorted signals that stem from a linear system with finite memory. Such a system is referred to as a finitestate machine (FSM), which is the general name given to a system (machine)
11. STATEMENT OF THE PROBLEM
, 1972
"... [6] H. Epheser and T. Schlomka, “Flachengrossen und elektrodynamische ..."
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