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Learning and Motivation State Fluctuations from Motoric and Neurophysiologic Metrics during a Somatosensory Task in Mice. [PDF]
Bueno-Junior LS +3 more
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Nonextensive Description of Charged-Particle Production in Ultrarelativistic Collisions. [PDF]
Rosales Herrera D +4 more
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Testing for Sufficient Follow-Up in Survival Data With a Cure Fraction. [PDF]
Yuen TP, Musta E.
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Navigating the unknown: Nanobubbles and the hidden complexity of aerophilic surfaces. [PDF]
Lü J.
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Asymptotic behavior of morphological filters
Journal of Mathematical Imaging and Vision, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lasse Koskinen, Jaakko Astola
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Codimension Sequences and their Asymptotic Behavior
Journal of Mathematical Sciences, 2021The authors study PI algebras over a field \(F\) of characteristic 0, and the numerical invariants associated to their T-ideals. The authors are among the leading specialists in the area. The paper surveys recent results concerning the asymptotic behaviour of the codimension sequence \(c_n(A)\) of a PI algebra \(A\).
Zaicev, M. V., Mishchenko, S. P.
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2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002
The algebraic constant modulus algorithm (ACMA) is a noniterative blind source separation algorithm. It computes jointly beamforming vectors for all constant modulus sources as the solution of a joint diagonalization problem. In this paper we analyze its asymptotic properties and show that (unlike the iterative CMA) it converges to the Wiener solution ...
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The algebraic constant modulus algorithm (ACMA) is a noniterative blind source separation algorithm. It computes jointly beamforming vectors for all constant modulus sources as the solution of a joint diagonalization problem. In this paper we analyze its asymptotic properties and show that (unlike the iterative CMA) it converges to the Wiener solution ...
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Asymptotic Behavior of Integrals
SIAM Review, 1972An account is given of some developments in the asymptotic evaluation of integrals of a single variable. After a discussion of Laplace integrals and quadrature formulas, estimates are provided of the errors in Laplace-type integrals and the method of steepest descents.
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