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Recovery of periodicities hidden in heavy-tailed noise
Illya M. Karabash
*
,
Jürgen Prestin
*
Corresponding author for this work
Institute of Mathematics
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Dive into the research topics of 'Recovery of periodicities hidden in heavy-tailed noise'. Together they form a unique fingerprint.
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Mathematics
Periodicity
100%
Recovery
98%
Random variable
71%
Convergence Theory
60%
Additive Noise
59%
Consistent Estimator
56%
Selection Procedures
56%
Complex Variables
53%
Unknown Parameters
47%
Fourier series
47%
Identically distributed
46%
Transform
37%
Singularity
35%
Unknown
33%
Derivative
31%
Estimator
30%
Coefficient
25%
Form
20%
Class
14%