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There are many efficient algorithms to compute linear model predictive control (MPC) optimization problems.
Over the years many efficient algorithms for the multiplierless design of multiple constant multiplications (MCMs) have been introduced.
There are many efficient algorithms for solving assignment problems.
Furthermore, many efficient algorithms are proposed to enable fast implementation [21, 24, 25].
Many efficient algorithms can replace the energy detection algorithm, and besides MO-LLR algorithm, many accurate algorithms can be used to detect the precise positions of the endpoints too.
Methods to extract relevant frequent itemsets from transactional data have been extensively studied, and many efficient algorithms are available.
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Many efficient iterative algorithms have been proposed to solve it.
Note that many efficient splitting algorithms rely on the fact that (operatorname{prox}_{f}) has a closed-form solution.
See Appendix D. Note that both subproblems, (26) and (27), are convex and represent standard problems for which many efficient (distributed) algorithms exist.
It is obvious that our proposed algorithm falls into the parallel splitting method since all the subproblems (3.1) can be solved in parallel by many existing efficient algorithms.
Among many efficient motion estimation algorithms, the FSBM algorithm with sum of absolute difference (SAD) is the most popular approach for motion estimation because of its considerably good quality.
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many efficient PBSAs
many efficient components
many efficient vectors
many efficient approaches
many efficient solutions
many efficient DMUs
many efficient techniques
many other algorithms
many efficient clusters
many efficient methods
many efficient bed-and-breakfasts
many existing algorithms
many efficient Anopheles
many efficient libraries
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