“…The application of a rectangular window can lead to its negative spectrum. Then, this phenom enon is absent as in the case of WF (31).…”
Section: The Gibbs Phenomenon and Kravchenko Weighting Functions Basementioning
confidence: 96%
“…We ask the following question: What PDF does the RQ (36) have? To answer this question, we use the property of the PDF of a sum of two RQs [30][31][32][33][34][35][36][37][38][39][40]. Let RQ X (Y) have PDF ( ).…”
Section: A the Probabilistic Properties Of Parent Atomic Functionmentioning
confidence: 99%
“…According to the definition [30][31][32][33][34][35][36][37][38][39][40] the ratio of third central moment m 3 to the cubed RMSD is called asymmetry A of RQ X. In our case A = 0.…”
Section: The Asymmetry Excess and Entropy Of A Random Quantity Hmentioning
confidence: 99%
“…≤ and ≤ Let us compare these results for the Gaussian It is known [30][31][32] that RQs are statis tically independent when joint density function p x of these quantities equals the product…”
Section: In Our Case the Entropy Ismentioning
confidence: 99%
“…The coefficients of series (65) are such that As moments, these coefficients are characteristics of a probability distribution they are called cumulants or semiinvariants [30][31][32]. Cumulants unambiguously determine RQs if series (65) converges for all ξ.…”
Section: E Cumulant Analysis Of the Kravchenko-rvachev Atomic Distrimentioning
The main physical applications of atomic, WA systems, and R functions are presented. The Whittaker-Kotelnikov-Shannon sampling theorem is generalized on the basis of atomic functions. Applica tions of atomic functions in the theory of probability and random processes, interpolation of stationary ran dom processes with atomic functions, and a new class of probabilistic weighting functions used in digital sig nal and image processing are considered.
“…The application of a rectangular window can lead to its negative spectrum. Then, this phenom enon is absent as in the case of WF (31).…”
Section: The Gibbs Phenomenon and Kravchenko Weighting Functions Basementioning
confidence: 96%
“…We ask the following question: What PDF does the RQ (36) have? To answer this question, we use the property of the PDF of a sum of two RQs [30][31][32][33][34][35][36][37][38][39][40]. Let RQ X (Y) have PDF ( ).…”
Section: A the Probabilistic Properties Of Parent Atomic Functionmentioning
confidence: 99%
“…According to the definition [30][31][32][33][34][35][36][37][38][39][40] the ratio of third central moment m 3 to the cubed RMSD is called asymmetry A of RQ X. In our case A = 0.…”
Section: The Asymmetry Excess and Entropy Of A Random Quantity Hmentioning
confidence: 99%
“…≤ and ≤ Let us compare these results for the Gaussian It is known [30][31][32] that RQs are statis tically independent when joint density function p x of these quantities equals the product…”
Section: In Our Case the Entropy Ismentioning
confidence: 99%
“…The coefficients of series (65) are such that As moments, these coefficients are characteristics of a probability distribution they are called cumulants or semiinvariants [30][31][32]. Cumulants unambiguously determine RQs if series (65) converges for all ξ.…”
Section: E Cumulant Analysis Of the Kravchenko-rvachev Atomic Distrimentioning
The main physical applications of atomic, WA systems, and R functions are presented. The Whittaker-Kotelnikov-Shannon sampling theorem is generalized on the basis of atomic functions. Applica tions of atomic functions in the theory of probability and random processes, interpolation of stationary ran dom processes with atomic functions, and a new class of probabilistic weighting functions used in digital sig nal and image processing are considered.
A closed form analytic representation of multidimensional periodic functions with a finite Fou rier spectrum is obtained as a modified interpolation series with a finite number of terms. The corresponding theorem is formulated, and the multidimensional periodic kernel of the expansion is analyzed. It is shown that such a representation makes it possible to calculate values of the derivatives of an arbitrary order of a peri odic function with a finite spectrum from the samples of this function.
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