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(1)

I nt. J. Math. Math.

Si.

Vol.

No.

2

(1980) 255-266

255

QUASI-CONVEX UNIVALENT FUNCTIONS

K.

INAYAT NOOR

and

D.K. THOMAS

Kerman University P. O. Box 182

Kerman, Iran

University College of Swansea SWANSEA SA2 8PP, Wales

(Received May 9, 1979 and

n

Revised form in June 25, 1979)

ABSTRACT. In this paper, a new class of normalized univalent functions is intro- duced. The properties of this class and its relationship with some other sub- classes of univalent functions are studied. The functions in this class are close- to-convex.

1980

MATHEMATICS SUBJECT CLASSIFICATION CODES:

Primary OA2;

Secondary

0A34

KEFWORDS AND PHRASES.

Univalent

functions,

Quasi-nvex, Close-to-nvex.

1 INTRODUCTION

Denote by S the class of functions f which are regular and univalent in the

,

unit disc E and satisfy f(0) 0 and f’ (0) i. The subclasses S and C of star- like and convex functions respectively are well known and have been extensively

,

studied. S and C are connected by the basic property

(2)

,

f C if and only if zf’ e S (i.i)

The subclass K of S consisting of close-to-convex function is also well

,

known and many of the properties of S can be extended to the wider class K.

The purpose of this paper is to introduce a natural analogue of the class C

in terms of the property defined in (i.i).

2. MAIN RESULTS.

Def. Let f be regular in

E

with f(O) 0 and f’(0) I. Then f is said to be quasi-convex in

E

if there exists a convex function g with g(0) 0, g’(0) 1 such that for z e

E,

Re

.(zf’

(z))’

g’ (z)"

> 0. (2.2)

Denote the class of quasi-convex functions by Q.

It is clear that when f(z) g(z), C Q so that C c Q. We show first that Q c K, so that every quasi-convex functions is univalent.

THEOREM I. Let f e Q. Then, for z e

E,

Re

__zf..’.(z).

> 0

g(z)

and so Q c K c S thus, every quasi-convex function is close-to-convex and hence univalent in

E.

PROOF: A result of Libera [4] shows that, if s and t are functions re-

,

gular in E with s(0) t(0) 0 and t e S then for z E,

Re

__s.’_(z)

> 0 + Re s(z)

> O.

t’(z) t(z)

An immediate application of this with s(z) zf’ (z) and t(z) g(z) proves

(3)

QUASI-CONVEX UNIVALENT FUNCTIONS 257

Theorem i.

It follows at once from the definition that

f Q if and only if zf’ e K. (2.2)

We can thus write

C

>

S

Q

>

K

where the direction of the arrow indicates set inclusion.

Theorem i shows that the image domain for all f e Q is close-to-convex.

However a specific characterisation of the image domain for f e Q remains an open question.

we

state now some basic properties of quasi-convex functions which can easily be extended from the class of convex functions. We omit the proofs as they are simple extensions from the convex case.

THEOREM 2. Let f e Q with f(z) z

+

anzn Then for

zl

r < i,

n=2

(i)

lanl

< i, n 2,3,...,

(+/-i) 2-<

If’(z)

< 2

(l+r) (l-r)

(iii) r <_

If (z)

-< l-rr l+r

(iv) w > 1/2 where

f(z)+

w in E

All inequalities are sharp, equality being attained for

f0(z)

l-zZ

(4)

We now give an example of a function in Q which is not convex.

Example 1 3 1 Let

fl

be the Koebe function; i e

fl(z)

(-z)z 2 Then

fl

maps E i-i conformally onto the w-plane cut from- to along the

x+

z

negative real axis. Let

f2:f2

"(z) l+xz x E. Then

f2

maps E onto it-

self and takes the origin onto the point x. Define

f3

by

f3(z) fl[f2(z)] fl(x) f3(0)

0 and

f3"

(0) 0 (since

f3

is univalent), and let

f4

f3

(z)

f4

(z)

f’0---

z E.

Combining all these transformations, we can write

fl +_z )_ fl(x

F(z)

+

xz

f

(x)

(-Ix i)

z (i- z)2

The function F is close-to-convex. In fact,

fl/X+

z

F’(z)

1 + .z/

fl(x)

(i

+ x--z)2

F"(z)

F’

(z)

(i

+

xz)

and

(5)

OUASI-CONVEX

UNIVALENT FUNCTIONS

zF"(z)

F’

(z)

,,!x +

z

1

x+z

i

+z

f

x+z I

(x+z) (i +xz)

2xz

z(, .- 1,* lz).

(x+ z) (i +xz) +i

,,/x+z

fl )("

z(-

xl +

,/" +_

z

)l (-,-z)" (,,,z)

fl [l+xz

/

(x+z) (t+xz)

i+

)z

fl

(x+z)

(l+x--z)

(x+z)

(.iz)

Le

ie i8 2

ie x

+

re

i

re (i-

z re r

I e d8 dq).

is

)

1

+

x re (x

+

re (i

+

xre

For Now,

and

2

with

(i

<

2

), we have correspndlng

81

and 82 with

(I

ie

F"(rei)

} ( f’()} rlei

Re

+

re d8 Re i+ d

;

F’

re

18) fl

()

’i+ rlei f-[ (rlei@)}

Re

----’) d

fl

(6)

Hence, for 0 1 and

81

< 82,

i8

F_’:(

re

iS)I

d8

F’

(re

i8)

02

i

fM(rl ei

Re 1+

rle

I

fl (rlei )i

de >

-

which shows that f e K.

Now,

+ x+

l+z z)

F’

(z)

l+xz 1

+

l+x

l+xZ!

i- l-x

(i -x)3 i (i +x)

(l+xz)2

(1

+

(i z)3

l+x

,

i- x

=z

B=I+x 1-’x

Intergrating, we have for z e E,

’F(z)

z(l

+

--

z)

(i z)

We notice that F maps E onto the w-plane cut along a half-line

".

nce

the choice of the point x in E is arbitrary, we can select x in such a way that the half-line does not pass through the origin in F(E), which

means F is not, in general, starlike. Because of relationships (3) and (1) between the classes Q and K and S we conclude that, in general,

(7)

QUASI-CONVEX UNIVALENT FUNCTIONS 261 2

the function

f,

defined in E by

f,(z)

F () d belongs to Q but not to 0

C.

3. SOME GROWTH PROBLEMS

Clunle and Keogh [i] showed that, if f C with f(z) z

+

n=2

.

a zn and fCE) has finite area. Then n a o(I) as n / and the exponent Is best pos-

n

slble. We extend this result to quasl-convex functions.

THEOREM 3. Let f Q with f(z) z

+

a zn If f(E) has finite area, then n=2 n

n a o(1) as n +

,,

the index of n being 5est possible.

n

PROOF: We use a modified version of themethod of Clunie and Pommerenke [2].

By (2), we can write

(zf’(z))’ g’(z)h(z),

where Re h(z) )0 for z E and h(0) i. Thus,

z(zf’(z))’ 2zg’(z) Reh(z)

zg’

(z) h(z), and so with z rei8 0 < r < i, Cauchy’s formula gives for n > I

2 1

n a z(zf’

(z))’e-nSd8

n 21[rn 0

21[ _in0

d

1 zg’(z)Re h (z)e O-

1[rn 0 Since Re h(z) > 0 for a E,

21[

n21a

n -< in

J [zg’(z) IRe

h(z) dO

+

i

1[r 0 21[rn

21[

I zg

2rn 0

’(z) h(z)e-in0dO.

21[

’(z) h(z)eIn0 dO (3.2)

(8)

Re[z(zf,(z)),e-larg zg’(z)]

from (3.1), and so inte- grating the first of the above two integrals by parts we have

1

[zg’(z) IRe

hCz)dO Re 1 z(zf’Cz))

’e-larg

z

g’ (z)de

--

2/[ -i arg z

g’ (Z)de

e

Re

----I

zf’(z)e z g

wrn 0

(z))

Also, zg’(z) h(z)

z(zf,(z)),e-21

arg z g’(z) and so (3.2) and (3.3) give 2

n

[a n]

-<

--n

r Re f’(z)e -i arg g

’(z) do(arg

Z g’(z))

i 2r2n

2/[

-2i arg z

g’(Z)do

zn+l

(’f’

(z))’e 0

1 1

II

+ -12

say.

n 2n

r

(3.4)

To estimate

II,

we note that, since f is regular in E and the area of

f(E) is finite, M(r,f’)

0.(i)

as r- i

1 -r

2

where M(r,f)

xl(reiS.) I-

Since d0 (arg z g’(z)) 2, we have 0

o(I) as r + i.

I1

1-r

(9)

OUASI-CONVEX

UNIVALENT FUNCTIONS 263

Integrating

12

by parts gives

12

2 Fn(z)e-2i arg z

g’ (Z)Re(zg’ (z))’

d0

0 g’(z)

where

z

Fn(Z)

tn (tf’(t))’dt

zn+if’(z) -nfn(Z),

0

and

z

f (z)

tnf

’(t)dt.

0

Now

r

IF

n (z) <

rn+iM(

tn

r,f’)

+

nM(r,f’) dt 0

<

2rn+iM(r,

f’).

2w

dO 2, we have

(z’

(z))_’

Since Re

(z) g 0

12

<

8rn+iM(r,f,)_. o(I)i

-r as r + i as before.

Finally, choosing r 1- i in (3.4) the estimates for I

I and

12

give

n

na o(i) as n / and Theorem 3 is proved.

n

An examination of the proof of Theorem 3 gives

COROLLARY: Let f e Q, Er {z:

Izl

r < i} and A(r) be the area of

f(Er).

Then, for n > 2,

(10)

n[anl

0(i) A(I

1_)%

n (3.5) We remark that (3.5) holds for the class S

,

but appears still to be an open

problem for the class K.

Denote by C(r) the closed curve which is the image of f(E

r)

and by L (r) the

length of C(r). We prove

THEOREM 4. Let f e Q. Then, for 0 < r ,e i,

2/(A(r))

< L(r) < 2/

(A(/r))

(io

l/_r

Further, if A(r) < for 0 < r < i, then

L(r) o(i)

(lo_ir)1/2

as r +. I.

PROOF: The left hand inequality follows atonce. from the isoperlmetrlc in- equality. Since f e Q, F(z) zf’ (z) is close-to-convex. Thus from [3,p.45]

2 2

LCr)

[zf

(z)

ld0 [(z);d0

0 0

r

< 2 M(;),zf’)

d;)

0

n=l

n=l

n

/

i-1/2

2/(A(/r)

io

ig_r

(11)

QUASI-CONVEX UNIVALENT FUNCTIONS 265

If a(r) < for 0 < r < I, then from (3.7)

L(r)--" 2

[ la

n

Ir

n

n=l N

< 2 n=l

[ lanlr

n

+

n=N

[ nlanl

2n 1/2

21/2 r

n

n=l N

2 n=l

[ lanlrn +

N

logl#r2

1 1/2

where

N

/ 0 as N / Thus L(r) o(i)

Io

"as r /i.

1 1 1/2

The convex function

fl

(z)

log_z

shows that the factor

lOl-r

in

(3.6) is best possible.

For f e C it is well know that L(r) < 2M(r). It follows from (3.6) that for f e Q, L(r) 0(i) M(r)

log_r

as r/l. The question of whether the factor

io

can be removed remains open.

In conclusion, we remark that other results for the class C can be extended to quasi-convex functions, often with only minor alterations in the proof. The objective of this paper has been to introduce the class Q, exhibit its basic properties and give some results whose proofs are not trivial extensions from the class C.

(12)

REFERENCES

i. CLUNIE,J.G. and KEOGH, F.R., "On starlike and convex schlicht functions", J. London Math.Soc., 35 (1960), 229-233.

2. CLUNIE, J.G. and POMMERENKE, Ch., "On the coefficients of close-to-convex univalent functions", J. London Math.Soc., 41 (1966),161-165.

3. HAYMAN, W.K., ’Multivalent functions’ Cambridge, 1967

4 LIBERA, R.J "Some classes of regular univalent functions" Proc.Amer Math Soc., 16 (1965), 755-758.

(13)

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/.

Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Track- ing System athttp://mts.hindawi.com/, according to the fol- lowing timetable:

Manuscript Due December 1, 2008 First Round of Reviews March 1, 2009 Publication Date June 1, 2009

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;

[email protected]

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]

Hindawi Publishing Corporation http://www.hindawi.com

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