Results 281 to 290 of about 1,437,104 (331)

Adaptive airspace allocation model for urban drone logistics using multi-objective optimization under uncertainty. [PDF]

Sci Rep
Zhu Y, Sun X, Hou T.
europepmc   +1 more source

CCMIM: Optimizing concrete defect detection through state-space modeling and dynamic feature fusion. [PDF]

PLoS One
Li X.
europepmc   +1 more source

A Hybrid Low-Complexity WMMSE Precoder with Adaptive Damping for Massive Multi-User Multiple-Input Multiple- Output Systems. [PDF]

Sensors (Basel)
Sen V, Deng H, Xu X, Shen M.
europepmc   +1 more source

Recursive Batch Smoother with Multiple Linearization for One Class of Nonlinear Estimation Problems: Application for Multisensor Navigation Data Fusion. [PDF]

Sensors (Basel)
Stepanov O, Isaev A, Dranitsyna E, Litvinenko Y.   +3 more
europepmc   +1 more source

Calculation of Computational Complexity for Radix-2 (p) Fast Fourier Transform Algorithms for Medical Signals.

, 2013
Rassoul Amirfattahi
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Computational sample complexity

Proceedings of the tenth annual conference on Computational learning theory - COLT '97, 1997
Summary: In a variety of PAC learning models, a trade-off between time and information seems to exist: with unlimited time, a small amount of information suffices, but with time restrictions, more information sometimes seems to be required. In addition, it has long been known that there are concept classes that can be learned in the absence of ...
Decatur, Scott E., Goldreich, Oded, Ron, Dana   +2 more
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Computational Complexity and Knowledge Complexity

SIAM Journal on Computing, 1998
Summary: We study the computational complexity of languages which have interactive proofs of logarithmic knowledge complexity. We show that all such languages can be recognized in \({\mathcal {BPP}}^{\mathcal {NP}}\). Prior to this work, for languages with greater-than-zero knowledge complexity only trivial computational complexity bounds were known ...
Goldreich, Oded, Ostrovsky, Rafail, Petrank, Erez   +2 more
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Amortized Computational Complexity

SIAM Journal on Algebraic Discrete Methods, 1985
A powerful technique in the complexity analysis of data structures is amortization, or averaging over time. Amortized running time is a realistic but robust complexity measure for which we can obtain surprisingly tight upper and lower bounds on a variety of algorithms. By following the principle of designing algorithms whose amortized complexity is low,
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Computational Complexity

2008
Complexity theory is a central field of the theoretical foundations of computer science. It is concerned with the general study of the intrinsic complexity of computational tasks; that is, it addresses the question of what can be achieved within limited time (and/or with other limited natural computational resources).
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