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Upper-Lower Bounded-Complexity QRD-M for Spatial Multiplexing MIMO-OFDM Systems

Manar Mohaisen, KyungHi Chang
2010 Wireless personal communications  
In this paper, we introduce an upper-lower bounded-complexity QRD-M algorithm (ULBC QRD-M).  ...  In the proposed algorithm we solve the problem of high extreme complexity of the conventional sphere decoding by fixing the upper bound complexity to that of the conventional QRD-M.  ...  Section 4 presents the proposed ULBC QRD-M algorithm with derivation of the upper and lower bound complexities in details.  ... 
doi:10.1007/s11277-010-0014-8 fatcat:xjev7udz5jfblh3ryenbf3dwka

Time Dependent Contraction Hierarchies -- Basic Algorithmic Ideas [article]

Peter Sanders
2008 arXiv   pre-print
This is the first hierarchical speedup technique for time-dependent routing that allows bidirectional query algorithms.  ...  Contraction hierarchies are a simple hierarchical routing technique that has proved extremely efficient for static road networks.  ...  For shortcuts that are actually introduced, we compute both upper and lower bounds. For comparing a shortcut a with a witness b, we compare a lower bound for a with an upper bound for b.  ... 
arXiv:0804.3947v1 fatcat:pkipeihnnjdg3aakvwkiu73kv4

Cooperative Graph Search Using Fractal Decomposition

James R. Riehl, Joao P. Hespanha
2007 American Control Conference (ACC)  
We use best-case and worst-case instances of the decomposed problem to establish upper and lower bounds on the optimal search reward, and the bounds are determined with much less computation than what  ...  We present an algorithm based on hierarchical decomposition that finds close-to-optimal search paths for a cooperative team of agents searching for one or more targets on a graph.  ...  The cost of these paths is 110 seconds, and the searchers collect a reward of 0.29, which lies between the worst-case lower bound of 0.26 and best-case upper bound of 1.0.  ... 
doi:10.1109/acc.2007.4282776 dblp:conf/acc/RiehlH07 fatcat:tavlqj3fcrcpdgz2skddxtsnai

Classifying the Heterogeneous Multi-Robot online search problem into quadratic time competitive complexity class

Shahar Sarid, Amir Shapiro, Elon Rimon, Yael Edan
2011 2011 IEEE International Conference on Robotics and Automation  
Hence, we obtain both an upper and lower bound on the time competitive complexity of the search problem. Consequently, H-MRSTM is proved to be optimal.  ...  Simulations in various environments show that the average case performance of H-MRSTM is superior to that of homogeneous multi-robot and single robot algorithms.  ...  If a time competitive upper bound f (t opt ) and a universal lower bound g(t opt ) for P are the same function up to constant coefficients, this function is the time competitive complexity class of P .  ... 
doi:10.1109/icra.2011.5980514 dblp:conf/icra/SaridSRE11 fatcat:wd67gopfbnhrncts5ebepf4haq

Page 6641 of Mathematical Reviews Vol. , Issue 90K [page]

1990 Mathematical Reviews  
We concentrate on two open problems: the average complexity of successful search (all moments) in an asymmetric multiway digital search tree, and the average complexity of unsuccessful search (all moments  ...  We also give a simpler and more direct derivation of J. W. Hong and H. T. Kung’s lower bound for the FFT for the special case B = P = O(1).” 90k:68030 68P10 Baeza-Yates, Ricardo A.  ... 

COMPETITIVE COMPLEXITY OF MOBILE ROBOT ON-LINE MOTION PLANNING PROBLEMS

YOAV GABRIELY, ELON RIMON
2010 International journal of computational geometry and applications  
Given an on-line task, its competitive complexity class is a pair of lower and upper bounds on the competitive performance of all on-line algorithms for the task, such that the two bounds satisfy the same  ...  The critical parameter in such problems is physical motion time which corresponds to length or cost of the path traveled by the robot.  ...  We define the competitive complexity class of a task P as a pair of lower and upper bounds on the competitive performance of all on-line algorithms for P , such that the two bounds satisfy the same functional  ... 
doi:10.1142/s0218195910003293 fatcat:3vyfqlogyfdsrcysugak5phoia

Competitive Complexity of Mobile Robot On Line Motion Planning Problems [chapter]

Yoav Gabriely, Elon Rimon
2005 Springer Tracts in Advanced Robotics  
Given an on-line task, its competitive complexity class is a pair of lower and upper bounds on the competitive performance of all on-line algorithms for the task, such that the two bounds satisfy the same  ...  The critical parameter in such problems is physical motion time which corresponds to length or cost of the path traveled by the robot.  ...  We define the competitive complexity class of a task P as a pair of lower and upper bounds on the competitive performance of all on-line algorithms for P , such that the two bounds satisfy the same functional  ... 
doi:10.1007/10991541_12 fatcat:iiqz6zg6uzgfngfagvd3goooz4

A Lower Bound for the Query Phase of Contraction Hierarchies and Hub Labels and a Provably Optimal Instance-Based Schema

Tobias Rupp, Stefan Funke
2021 Algorithms  
For a variant of our instance-based schema applied to some special graph classes, we can even show matching upper and lower bounds.  ...  We prove a Ω(n) lower bound on the query time for contraction hierarchies (CH) as well as hub labels, two popular speed-up techniques for shortest path routing.  ...  Acknowledgments: We like to thank the OpenStreetMap community for making free geodata available for our experiments. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/a14060164 fatcat:cwzbxc7twfdxxh2m22zxihj64q

The worst case complexity of McDiarmid and Reed's variant of BOTTOM-UP HEAPSORT is less than n log n + 1.1n

Ingo Wegener
1992 Information and Computation  
We remark that 3 -A(n) -CI < 0.979378 and 3 -A(n) -0: ,< 0.893306 for n = 2k. The difference between upper and lower bound for the average case complexity of MDR-HEAPSORT is only l.5n + log n.  ...  THE AVERAGE CASE ANALYSIS Theorem 1, is, of course, also an upper bound on the average case complexity of MDR-HEAPSORT.  ... 
doi:10.1016/0890-5401(92)90005-z fatcat:pgmgz7xo7zeivpzvt3kqg44hey

Upper and Lower Bounds for Randomized Search Heuristics in Black-Box Optimization

Stefan Droste, Thomas Jansen, Ingo Wegener
2004 Theory of Computing Systems  
Lower bounds on the black-box complexity of problems are derived without complexity theoretical assumptions and are compared to upper bounds in this scenario.  ...  However, for most problems the best worst-case expected run times are achieved by more problem-specific algorithms. This raises the question about the limits of general randomized search heuristics.  ...  A similar reason holds for the difference in the lower and upper bound for RUN.  ... 
doi:10.1007/s00224-004-1177-z fatcat:35rrbg5zkbabdgk6qc64uhw2lm

On the improved path metric for soft-input soft-output tree detection

Jun Won Choi, Byonghyo Shim, Andrew C. Singer
2010 2010 Information Theory and Applications Workshop (ITA)  
While the conventional path metric accounts for the contribution of symbols on a visited path due to the causal nature of tree search, the new path metric, called improved path metric, reflect the contribution  ...  We study the probability of correct path loss (CPL) for the improved path metric and confirm the performance improvement over the conventional path metric.  ...  Hence, the terms B upper k and B lower k represent the upper-bound and lower-bound of the SINR gain achieved by the improved path metric, respectively.  ... 
doi:10.1109/ita.2010.5454143 dblp:conf/ita/ChoiSS10 fatcat:iefdlar6vjhplojgr3zhzl3qni

Tightest constraint first: An efficient delay sensitive multicast routing algorithm

Gang Feng
2005 International Journal of Communication Systems  
Among all the previously proposed algorithms, the bounded shortest path algorithm (BSMA) [22] have been proved to be capable of producing a multicast tree that has on average the lowest cost.  ...  TCF runs a DCLC heuristic only once for each destination and therefore has a provably low time complexity.  ...  By replacing p with r and updating the cost upper bound, the algorithm can continuously search for better solutions until no feasible path is returned by H DCC.  ... 
doi:10.1002/dac.728 fatcat:xynmhw4gyneabi3vixhpnipida

Nested performance bounds and approximate solutions for the sensor placement problem

Muhammad Sharif Uddin, Anthony Kuh, Aleksandar Kavcic, Toshihisa Tanaka
2014 APSIPA Transactions on Signal and Information Processing  
Finally, we show through simulations that the approximate algorithms perform well and provide tight implementable lower bounds to optimal performance and the nested bounds provide upper bounds to optimal  ...  time in the number of parameters and derives a set of analytical nested performance upper bounds to the optimal solution based on the structure of the data correlation matrix.  ...  Figure 1 shows the average efficacies and the upper bounds, averaged over 100 realizations.  ... 
doi:10.1017/atsip.2014.3 fatcat:qhomcc23a5aj7h7e63focby7b4

CBUG: A Quadratically Competitive Mobile Robot Navigation Algorithm

Y. Gabriely, E. Rimon
2008 IEEE Transactions on robotics  
The CBU G algorithm achieves the quadratic lower bound and thus has optimal competitiveness.  ...  The competitiveness of an on-line navigation algorithm measures its path length relative to the length of the optimal off-line path.  ...  If a competitive upper bound f (l opt ) and a universal lower bound g(l opt ) for P are the same function up to constants, this function is the competitive complexity class of P .  ... 
doi:10.1109/tro.2008.2006237 fatcat:twojsvcv4jdo5oesewh4yrij4q

Embeddings and labeling schemes for A* [article]

Talya Eden, Piotr Indyk, Haike Xu
2021 arXiv   pre-print
A* is a classic and popular method for graphs search and path finding.  ...  In particular, we consider heuristics induced by norm embeddings and distance labeling schemes, and provide lower bounds for the tradeoffs between the number of dimensions or bits used to represent each  ...  Figure 2 : 2 Figure 2: Average-case complexity lower bound instance for l 8 norms. Figure 3 : 3 Figure 3: Average-case complexity lower bound instance for labeling.  ... 
arXiv:2111.10041v1 fatcat:fgm2w7bvajfynoazd2b3yev7qm
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