Results 151 to 160 of about 18,163 (201)

Provable Preconditioned Plug-and-Play Approach for Compressed Sensing MRI Reconstruction. [PDF]

IEEE Trans Comput Imaging
Hong T, Xu X, Hu J, Fessler JA.
europepmc   +1 more source

Remaining Useful Life Prediction Method for Bearings Based on Pruned Exact Linear Time State Segmentation and Time-Frequency Diagram. [PDF]

Sensors (Basel)
Wei X, Fan J, Wang H, Cai L.
europepmc   +1 more source

Optimizing Sensor Data Interpretation via Hybrid Parametric Bootstrapping. [PDF]

Sensors (Basel)
Golovko VV.
europepmc   +1 more source

An application of the Mittag-Leffler-type Borel distribution and Gegenbauer polynomials on a certain subclass of bi-univalent functions. [PDF]

Heliyon
Hussen A.
europepmc   +1 more source

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Reversion of Chebyshev’s Inequality

Theory of Probability & Its Applications, 1996
Summary: In terms of the moment-generating function of a random variable, we derive a lower bound for the tail of its distribution without an excursion into the complex domain.
Bagdasarov, D. R., Ostrovskij, E. I.
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On Bernstein Inequality via Chebyshev Polynomial

Computational Methods and Function Theory, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Chebyshev’s inequality for Choquet-like integral

Applied Mathematics and Computation, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sheng, Changtao, Shi, Jiuliang, Ouyang, Yao   +2 more
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Chebyshev inequalities in symmetric spaces

Mathematical Notes of the Academy of Sciences of the USSR, 1971
The characterization (by means of inequalities) of some special Banach spaces is investigated.
Kuricyn, Ju. G., Petunin, Ju. I., Semenov, E. M.   +2 more
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Continuous Generalizations of Chebyshev’s Inequality

Theory of Probability & Its Applications, 1958
Let $x(t)$ be a random function with known ${\bf E}[x(t)]$ and ${\bf E}[x(t)x(s)]$, $0 \leqq s$, $t \leqq 1$. In Section 3 a bound is given for the probability that $|x(t)|$ exceeds the given function $\alpha (t)$ at least for one t. The bound involves an arbitrary quadratic form, which can be selected in an appropriate way giving certain bounds (see ...
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Chebyshev Inequalities for Unimodal Distributions

The American Statistician, 1997
Abstract Let g be an even function on ℝ that is nondecreasing on [0, ∞), and let k be a positive constant. For random variables X that are unimodal with mode 0, and for random variables X that are unimodal with an unspecified mode, we derive sharp upper bounds on P(|X| ≥ k) in terms of Eg(X).
Thomas M. Sellke, Sarah H. Sellke
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