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Discrete Sampling and Interpolation: Universal Sampling Sets for Discrete Bandlimited Spaces [PDF]

open access: yesIEEE Transactions on Information Theory, 2012
We study the problem of interpolating all values of a discrete signal f of length N when ...
Osgood, Brad   +2 more
core   +2 more sources

Accelerated Stochastic Sampling of Discrete Statistical Systems [PDF]

open access: yesPhysical Review E, 2010
We propose a method to reduce the relaxation time towards equilibrium in stochastic sampling of complex energy landscapes in statistical systems with discrete degrees of freedom by generalizing the platform previously developed for continuous systems ...
A. F. Voter   +9 more
core   +3 more sources

The Flash-Lag, Fröhlich and Related Motion Illusions Are Natural Consequences of Discrete Sampling in the Visual System [PDF]

open access: yesFrontiers in Psychology, 2018
The Fröhlich effect and flash-lag effect, in which moving objects appear advanced along their trajectories compared to their actual positions, have defied a simple and consistent explanation.
Keith A. Schneider
doaj   +2 more sources

Sampling with discrete contamination [PDF]

open access: yes, 2011
The sampling variance for a process stream which carries fluctuating levels of the sought-after analyte and is subject to mass flow variation can be estimated from the covariance function of the analyte fluctuation and the covariance function of the ...
Bourgeois, Florent, Lyman, Geoffrey
core   +3 more sources

Analytical formulas for pricing discretely-sampled skewness and kurtosis swaps based on Schwartz’ s one-factor model [PDF]

open access: yesSongklanakarin Journal of Science and Technology (SJST), 2021
In this paper, analytical formulas for pricing discretely-sampled skewness and kurtosis swaps based on the Schwartz’s one-factor model is derived by applying the results of the conditional moments proposed by Chumpong, Mekchay, and Rujivan (2019).
Kittisak Chumpong   +2 more
doaj   +1 more source

Sampling Discretization of Integral Norms [PDF]

open access: yesConstructive Approximation, 2021
The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. Even though this problem is extremely important in applications, its systematic study has begun recently.
Dai, F.   +4 more
openaire   +3 more sources

Universal Sampling Discretization

open access: yesConstructive Approximation, 2023
Let $X_N$ be an $N$-dimensional subspace of $L_2$ functions on a probability space $( , )$ spanned by a uniformly bounded Riesz basis $ _N$. Given an integer $1\leq v\leq N$ and an exponent $1\leq q\leq 2$, we obtain universal discretization for integral norms $L_q( , )$ of functions from the collection of all subspaces of $X_N$ spanned by $v ...
Dai, F., Temlyakov, V.
openaire   +2 more sources

Discrete Gaussian Sampling [PDF]

open access: yesIEEE Transactions on Computers, 2019
In this chapter we propose an efficient hardware implementation of a discrete Gaussian sampler for ring-LWE encryption schemes. The proposed sampler architecture is based on the Knuth-Yao sampling Algorithm [10]. It has high precision and large tail-bound to keep the statistical distance below \(2^{-90}\) to the true Gaussian distribution for the ...
Sujoy Sinha Roy, Ingrid Verbauwhede
openaire   +3 more sources

Portfolio investment based on probabilistic multi-objective optimization and uniform design for experiments with mixtures

open access: yesVojnotehnički Glasnik, 2023
Introduction/purpose: In this paper, a new approach to solving the portfolio investment problem is formulated to handle simultaneous optimization of both maximizing the rate of return and minimizing the variance of the rate of return. Probability - based
Maosheng Zheng, Jie Yu
doaj   +1 more source

A new solution for solving a multi-objective integer programming problem with probabilistic multi-objective optimization

open access: yesVojnotehnički Glasnik, 2023
Introduction/purpose: In this paper, a new solution for solving a multiobjective integer programming problem with probabilistic multi – objective optimization is formulated.
Maosheng Zheng, Jie Yu
doaj   +1 more source

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