2023
DOI: 10.3390/fractalfract7080593
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L-Index in Joint Variables: Sum and Composition of an Entire Function with a Function With a Vanished Gradient

Abstract: The composition H(z)=f(Φ(z)) is studied, where f is an entire function of a single complex variable and Φ is an entire function of n complex variables with a vanished gradient. Conditions are presented by the function Φ providing boundedness of the L-index in joint variables for the function H, if the function f has bounded l-index for some positive continuous function l and L(z)=l(Φ(z))(max{1,|Φz1′(z)|},…,max{1,|Φzn′(z)|}),z∈Cn. Such a constrained function L allows us to consider a function Φ with a nonempty … Show more

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Cited by 4 publications
(2 citation statements)
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“…Moreover, the functions of bounded l-index (and bounded index, if l ≡ 1) have applications in the analytic theory of differential equations [15,[28][29][30] and the value distribution theory [17,22,24]. One-dimensional Sheremeta-Kuzyk's approach developed in two multidimensional subapproaches: bounded L-index in direction [9] and bounded L-index in joint variables [10]. A notion of bounded index for bivariate entire functions [23,25]) matches with the notion of bounded L-index in joint variables, if L ≡ (1, .…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, the functions of bounded l-index (and bounded index, if l ≡ 1) have applications in the analytic theory of differential equations [15,[28][29][30] and the value distribution theory [17,22,24]. One-dimensional Sheremeta-Kuzyk's approach developed in two multidimensional subapproaches: bounded L-index in direction [9] and bounded L-index in joint variables [10]. A notion of bounded index for bivariate entire functions [23,25]) matches with the notion of bounded L-index in joint variables, if L ≡ (1, .…”
Section: Introductionmentioning
confidence: 99%
“…Íàñàìêiíåöü çàçíà÷èìî, ùî Ì. Ì. Øåðåìåòà [54,96,106] òàêîae ó ðàìêàõ òåîðiô óíêöié îáìåaeåíîãî iíäåêñó ïåðøèì ïî÷àâ âèâ÷àòè óìîâè, çà ÿêèõ êîìïîçèöiÿ àíà-ëiòè÷íèõ ôóíêöié ìàòèìå îáìåaeåíèé iíäåêñ. Öÿ åñòàôåòà äîñëiäaeåííÿ êîìïîçèöié ó áàãàòîâèìiðíîìó âèïàäêó âiä íüîãî ïiäõîïëåíà ó ñòàòòÿõ [28,30,43].…”
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