Good Linear Operators and Meromorphic Solutions of Functional Equations
Author(s) -
Nan Li,
Risto Korhonen,
Lianzhong Yang
Publication year - 2015
Publication title -
journal of complex analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.167
H-Index - 7
eISSN - 2314-4963
pISSN - 2314-4971
DOI - 10.1155/2015/960204
Subject(s) - algorithm , meromorphic function , computer science , artificial intelligence , mathematics , mathematical analysis
Nevanlinna theory provides us with many tools applicable to the study of value distribution of meromorphic solutions of differential equations. Analogues of some of these tools have been recently developed for difference, q-difference, and ultradiscrete equations. In many cases, the methodologies used in the study of meromorphic solutions of differential, difference, and q-difference equations are largely similar. The purpose of this paper is to collect some of these tools in a common toolbox for the study of general classes of functional equations by introducing notion of a good linear operator, which satisfies certain regularity conditions in terms of value distribution theory. As an example case, we apply our methods to study the growth of meromorphic solutions of the functional equation M(z,f)+P(z,f)=h(z), where M(z,f) is a linear polynomial in f and L(f), where L is good linear operator, P(z,f) is a polynomial in f with degree deg P≥2, both with small meromorphic coefficients, and h(z) is a meromorphic function
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom