Internat. J. Math. & Math. Sci.
VOL. 15 NO. 2 (1992) 413-415
413
A
NOTEON A FUNCTIONAL
INEQUALITYHORSTALZER
Department
ofPureMathematics Applies Mathematics andAstronomy
University of SouthAfrica
P.O. Box
392 0001 Pretoria,South Africa(Received
September25, 1990 andin revisedform March5,1991)
ABSTRACT.
We
prove: Ifrl,...,rk are(fixed)
positive real numbers withI’l
k rj>
1,then theonly entiresolutions"
C Cof thefunctionalinequalityare
,(z)
czn,
wherecisacomplexnumber andn s apositive integer.KEY WORDS AND PHRASES.
Functional inequality,entirefunctions.1991
AMS SUBJECT CLASSIFICATION CODE.
39C05.1.
INTRODUCTION.
Inspired byaproblemofH. Haruki, who askedforallentiresolutionsof
I(z + w)
2+ I(z w)
2+ 21 (0) 12 > 21 (z) 12 + 21 (w) 12 (.x)
J.
Walorski[1]
provedin1987 thefollowinginteresting proposition:Let r
>
1 bea(fixed)
real number. Then theonlyentire solutions qa:C--,Cof the functional inequality(z) >_
rI(z)
are
(z)
czn(1.2)
wherecECandnEN.
As
an application ofthistheorem,
Walorski showed that the only entire functions 0:C C satisfying(1.1)
ando(0)=
0arethe monomials(1.2).
Theaimofthisnoteis to proveanextension of Walorski’s result by using a method which is (slightly) different from the two approaches presentedin[1].
2.
MAIN RESULTS.
Theorem. Letrl, rk be
(fixed)
positive real numberswith I-[ rj>
1. Then the onlyentire j=l414 H. ALZER solutions
go:C
Cofk
]lrj)
I1 I,(,’.z) _> I,(z) : (2.1)
j= j=
arethefunctionsgo(z)+cz
n,
wherecisacomplex number andnisapositive integer.PROOF. Simple calculationsreveal that the functions go(z)=czn
(c
6_C,n6_N)
satisfy(2.1).
Next
weassumethatgo is an entiresolutionofinequality(2.1).
Becauseof
1"I
k rj>
1 weconclude from(2.1)
with z 0 that go has at 0a zero. Letn bethej=l
order ofthiszero;wedefine
f(z) go(z)/z
n(2.2)
then
/
isanentirefunction withf(0)
0.From (2.1)
weobtainH
k[f(r.z)[ >_( fi rJ.-n) lf(z)l t. (2.3)
j=l j=l
Wesuppose that
f
hasa zeroz0.By
inductionitfollows from(2.3)
thatzo/rrff
is arootoff
for allnon-negative integers m. From the identity theorem we conclude
f(z)--0
which contradicts the conditionf(0) #
0. Hencef
hasnozerowhichimplies that thefunctionis entire. From
(2.3)
weconcludef(z)
kH f(,..z)
j=1
(2.4)
rn.
Ig(z)l _<
111
j=
for allz6-
C,
and Liouville’stheorem implies thatg isaconstant. Thereforewehave
f(z) K
kiI f(r.z), K
6_C.j=l /
Since
f(O) #
0weget from(2.5): K
1;hence
/(z) =
j=lI f(,.z).
/ Differentiationleads toSetting
f’(z)
k=/E f(.z)
kf--
_- /f() =o
weobtainfrom
(2.7)
and(2.8):
E a"zm=E (a.,E rT+X)z,
rn=O rn=O j=l
(2.8)
(2.9)
FUNCTIONAL INEQUALITY 415
and comparing thecoefficientsofzmyields for allrn
>
0:k
kam=a
mj=lr n+l. (2.10)
Weassumethat thereexists anintegerm0
>
0 suchthatam
0
#
0, thenwegetfrom the arithmetic mean-geometricmeaninequality and from(2.10)"
+ 1]1/k
k m0jmo
+Ik
which contradicts the assumption rj
>
1.Hence,
am 0forallm>
0. Thisimplies thatf
isaj=l
constant, saycE
C,
andthereforeweobtainqo(z)
czn.
It is natural to look for all entire functions
"
C--. C which satisfy the following additive counterpartof inequality(2.1):
(-
j=l9(rjz)) > --j=l
r.I[o(z)[ (2.11)
k
where rl,...rk are
(fixed)
positive real numbers with.,rj>k.
The monomials3=1
(z) czn(c _ C,n _ N)
aresolutionsof(2.11).
Indeed,inequality(2.11)
with(z)
cznreducestok k
E r > E
rj,(2.12)
j=l
--j=l
k
which follows immediately from
Jensen’s
inequality and the assumptiony rj>
k.By
an j=largumentation similar to theone we haveused toestablish the theorem it can beshown that the functions
(z)cz" (c.C,n _)
are the only entire solutions of(2.11).
This provides another extensionof Walorski’s result./
If the expression on the left-hand side of
(2.11)
will be replaced byI(.)1,
then econclude from the triangle inequality that
(z)
czn(c _ C,
n_ )
alsosolve 3k k
j=l 3
--j=l
k
where rl,...,rk are
(fixed)
positive real numberswithy
rj>
k. We finish by asking:more solutionsof
(2.13) (if
k> 1)? J
(2.13) Are
thereREFERENCE
1.
WALORSKI, J.,
Onafunctionalinequality, AequationcsMath.
32(1987),
213-215.Journal of Applied Mathematics and Decision Sciences
Special Issue on
Intelligent Computational Methods for Financial Engineering
Call for Papers
As a multidisciplinary field, financial engineering is becom- ing increasingly important in today’s economic and financial world, especially in areas such as portfolio management, as- set valuation and prediction, fraud detection, and credit risk management. For example, in a credit risk context, the re- cently approved Basel II guidelines advise financial institu- tions to build comprehensible credit risk models in order to optimize their capital allocation policy. Computational methods are being intensively studied and applied to im- prove the quality of the financial decisions that need to be made. Until now, computational methods and models are central to the analysis of economic and financial decisions.
However, more and more researchers have found that the financial environment is not ruled by mathematical distribu- tions or statistical models. In such situations, some attempts have also been made to develop financial engineering mod- els using intelligent computing approaches. For example, an artificial neural network (ANN) is a nonparametric estima- tion technique which does not make any distributional as- sumptions regarding the underlying asset. Instead, ANN ap- proach develops a model using sets of unknown parameters and lets the optimization routine seek the best fitting pa- rameters to obtain the desired results. The main aim of this special issue is not to merely illustrate the superior perfor- mance of a new intelligent computational method, but also to demonstrate how it can be used effectively in a financial engineering environment to improve and facilitate financial decision making. In this sense, the submissions should es- pecially address how the results of estimated computational models (e.g., ANN, support vector machines, evolutionary algorithm, and fuzzy models) can be used to develop intelli- gent, easy-to-use, and/or comprehensible computational sys- tems (e.g., decision support systems, agent-based system, and web-based systems)
This special issue will include (but not be limited to) the following topics:
• Computational methods: artificial intelligence, neu- ral networks, evolutionary algorithms, fuzzy inference, hybrid learning, ensemble learning, cooperative learn- ing, multiagent learning
• Application fields: asset valuation and prediction, as- set allocation and portfolio selection, bankruptcy pre- diction, fraud detection, credit risk management
• Implementation aspects: decision support systems, expert systems, information systems, intelligent agents, web service, monitoring, deployment, imple- mentation
Authors should follow the Journal of Applied Mathemat- ics and Decision Sciences manuscript format described at the journal site http://www.hindawi.com/journals/jamds/.
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Guest Editors
Lean Yu,Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China;
Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;
Shouyang Wang,Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China; [email protected]
K. K. Lai,Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong; [email protected]
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