Applied Mathematics, 2011, 2, 1076-1090
doi:10.4236/am.2011.29149 Published Online September 2011 (http://www.SciRP.org/journal/am)
Copyright © 2011 SciRes. AM
Numerical Solution of Mean-Square Approximation
Problem of Real Nonnegative Function by the Modulus
of Double Fourier Integral
Petro Savenko, Myroslava Tkach
Pidstryhach Institute for Applied Problems of Mechanics and Mathematics, Lviv, Ukraine
E-mail: spo@iapmm.lviv.ua, tmd@iapmm.lviv.ua
Received May 27, 2011; revised June 21, 2011; accepted June 29, 2011
Abstract
A nonlinear problem of mean-square approximation of a real nonnegative continuous function with respect
to two variables by the modulus of double Fourier integral dependent on two real parameters with use of the
smoothing functional is studied. Finding the optimal solutions of this problem is reduced to solution of the
Hammerstein type two-dimensional nonlinear integral equation. The numerical algorithms to find the branching
lines and branching-off solutions of this equation are constructed and justified. Numerical examples are pre-
sented.
Keywords: Mean-Square Approximation, Discrete Fourier Transform, Two-Dimensional Nonlinear Integral
Equation, Nonuniqueness and Branching of Solutions, Two-Dimensional Nonlinear Spectral
Problem
1. Introduction
A variational problem about mean-square approximation
of a real finite function by the modulus of double Fourier
integral with use of smoothing functional [1] is studied.
The nonuniqueness and branching of solutions is an es-
sential feature of nonlinear approximation problem. The
problem of finding a set of branching points is insuffi-
ciently investigated nonlinear two-parameter spectral
problem. The existence of connected components of the
spectrum, which in the case of real parameters, similarly
as in [2], are spectral lines, is essential difference of
two-dimensional spectral problems compared with one-
dimensional ones.
The algorithms for finding the lines of possible bran-
ching of solutions of the Hammerstein type nonlinear
equation, which are based on implicit functions methods,
are proposed and justified. The algorithms for numerical
finding the optimal solutions of the approximation prob-
lem are constructed and justified also. Numerical exam-
ples are presented.
Note that this class of problems are widely used at
solving the inverse problems of radio physics, acoustics
and so on [3,4].
2. Problem Formulation, Basic Equations
and Relations
Consider the linear integral operator
 

12
112 2
,
,exp dd


G
fss AU
Uxyicxs cysxy
, (1)
which is the double Fourier transform of function
2
,UxyL G, dependent on the real two-dimen-
sional parameter
12
,ccc, 0i
c
1, 2i1.
Operator acts from space into the solid
angle
U

2
LG
2
L
, where 2
is some limited domain
in which a real continuous nonnegative and nonzero
function
12
,
F
ss is given. In the spaces
2
LG and
2
L
we introduce scalar products and generable by
them norms






2
2
2
2
121 2
12
12
4π
,,
,,

LG
G
LG
LG
UUUxyUxy xy
cc
UUU
,dd
(2)
1Parameters c1, c2 are physical parameters of the object being investi-
gated. In particular, in the antennas synthesis problems these parame-
ters characterize the electrical sizes of aperture of radiating system and
a solid angle in which the necessary energetic characteristic of radiation
is given [4].
P. SAVENKO ET AL.1077



2
1211221212
,,,
Ldd
f
ffssfss
 ss,


2
12
,L
fff
. (3)
Since the domain is limited, the integral in
(1) exists in the usual sense [5] for an arbitrary function
. Here the function
2
G

2
ULG
12
,
f
ss is continuous
and quadratically integrable.
Consider the problem about approximation of a real
continuous and nonnegative function
12
,
F
ss in the
domain by the modulus of the Fourier integral (1).
We shall formulate it as a minimization problem of the
smoothing functional

 
 
2
2
2
2
2
22
()
22
min
.

 
 
L
G
L
UL G
LG
L
UFAU U
Ff U
(4)
Here the first summand describes the mean-square de-
viation of the modulus of the Fourier integral from the
given function
12
,
F
ss in the domain . The second
summand imposes constraints on the norm of the Fourier
integral prototype,
is a weight (regularizing) pa-
rameter.
Equating the Hato differential of the functional (4) to
zero and taking into account (1), we write the equation
concerning the function U that describes the fixed
points in the space :

U

2
LG

argiAU
UAAUAFe

 , (5)
where
 

1122
12
12 12
2,e dd
2π
icxs cys
cc
A
ffss
 ss
is conjugate operator with
.
Further we introduce to shorten records the following
notations:

12
,Qss, , , .
12
dddQss

,PxydddPxy
Taking into account that a set of zeros
NA con-
sists only of zero element, and acting on both parts of (5)
by operator
A
, we obtain equivalent to (5) equation
with respect to function
12
,
f
ss in the space
G
2
L
if
arg
fAAfAAFe


. (6)
Accordingly to the introduced above notations this
equation in the expanded form takes the form


arg ()
,, ()d
,,e d,


 

 ifQ
f
Qf KQQfQQ
KQQ FQQ
Bc
c
(7)
where
 

12
111222
2
,,
expd d
(2π)





G
KQQ
cc icxs scyssxy
c
(8)
is a kernel dependent on the form of the domain . In
the case of symmetric domain (8) can be simplified.
In particular, if the axis is the axis of symmetry of
the domain and its upper and lower limits are de-
scribed, respectively, by the functions
G
G
OX
G
y
x
 at
1,1x , the kernel (8) is real and it has the form





1222
1
111
2
22
1
,,
sin
cosd .
2π

KQQ
cs sx
ccx ssx
ss
c
(9)
Lemma 1. Between solutions of Equations (5) and (6)
there exists bijection, that is if is the solution of (5) U
then
f
AU
is the solution of (6). On the contrary, if
f
is the solution of (6) then

11
exp aUAf Ff


 rgi
 is the solution
of (5).
Proof. Let U
be a solution of (5). Then
arg 0
iAU
UAA AFe
 

11
U

. Acting on this
equality by the operator
, we obtain
arg
11
iAU
AUAAAA Fe

 
0AU

. The ope-
rator acts from the space
2
LG into the space
2
L
,
and a set of its zeros consists only of zero element. Then
from the last identity follows that
2AU f

L is
a solution of the equation
arg
11 0
if
fAAfAAFe

 

, that is (6).
On the contrary, let

2
fL
be a solution of (6).
The operator
A
acts from the space into the
space

2
L
2
LG
[6], and the Hilbertian space 2
L
coin-
cides with the space [5]. From here follows, that
2
L
A
acts from the space into the space

2
L
G
2
L.
Taking into account that
F
and
f
are continuous
functions, the function
exp arg
F
i
f
is quadrati-
cally integrable in the domain . From here follows


11
2
exp argfFifL



.
Thus,


11
2
exp arg
A
fFifUL

 

 G
and the right part of (6) is a result of action of operator
on the element U
, that is


11
exp arg
A
UAAfF i ff

 

 .
Thus owing to the fact that
A
Uf
, we write this
equality in the form


11
exp arg0AUAAUAFiAU

 
 
.
Since a set of zeros of operator
consists only of
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.
1078
zero element we have


11
exp argUAAUAFiAU

 

 
.
So,
(10)


11
exp argUAfF i f



 
solves (5). Lemma is proved.
Using the general expression (8) for the kernel

,,cKQQ

,, dcDfAAfKQ QfQQ



we shall consider a self-adjoint operator
(11)
and corresponding to it quadratic form for arbitrary func-
tion :
 
2
fQ L
 
 

2
22
2
,,,d
exp,d d0.
2π



 
 
G
DffKQQf QQf QQ
cc fQiPQQP
c
c
d
This equality to zero is achieved only as
0fQ
.
From here follows that the operator is nonnegative
in [7] and, respectively, in
D

2
L

C. Based on
this property, the operator retains the nonnegative
functions cone
D

CK invariant, that is
[8].
DKK
Since a set of values of operator
is a set of con-
tinuous functions [5], belonging to the space
2
L
,
and a set of continuous functions in the domain
, is
dense in the space 2 [5], we shall investigate the

L
solutions of (6) in the space .

L
2
On the basis of decomplexification [7] we consider the
complex space

as a direct sum
 
CC  of two real spaces of continuous
functions in the domain . The elements of this space
have the form:

,
T
fuv,


ReufC,

ImvfC. Norms in
these spaces we shall introduce as:




 
max,max ,
max, .

 


CC
QQ
CC
uuQvv
fuv
Q
(12)
The Equation (6) in decomplexified space
we
reduce to equivalent to it system of equations
 
 
11
11112
11
22122
,,,
,,,
uBuvBu Buv
vBuvBvBuv






(13)
where

11 ,, dcBKQQuQ

 Q
,
 
 
12 22
,, dcuQ
BFQKQQ
uQ vQ



 
21 ,, dcBKQQvQ

 Q
,
 
 
22 22
,, dcvQ
BFQKQQ
uQ vQ
Q


 . (15)
Note, are linear integral operators and
11
B21
B
11 21
BB
.
Denote a closed convex set of continuous functions as
M
S supposing that



,:
:,
 
 
uvu u
vv
MM MMMC
MM
C
SSSSuS uqM
SvSvqM
,
where

 
1
1
11 ,
 

CC
qI B

max, ,dc
Q
M
FQ KQQQ



, (16)
I is a unit operator in ()C
.
We show that operator 12 determined by

,BT
BB
(13) acts in the space
Q
; (14)
. At first consider
,Buv
1.
The first component of this operator, defined by (14), is a
linear integral operator with the kernel
,,cKQQ
which is continuous on both arguments. Consequently,
11 :BCC
 is a continuous operator [9].
Show that

12 :B
. Let

,T
f
uv be
an arbitrary function belonging to

. For
0i
c

1, 2i the kernel is a con-
,,cKQQ
tinuous function with respect to its arguments in the
closed domain
. Then according to the Cantor
theorem [10]
,,cKQQ
is a uniformly continuous
function in
. From here follows: at fixed for
any points
c
11
,QQ
and
22
,QQ
such that whenever
112 2
,,Q QQQ

, then
 
112 2
,,, ,ccKQQKQ Qa

, here
daFQQ
 .
On this basis we have
 

 

12
12
22
,, ,,
d
d
uQ uQ
FQKQQKQ Q
uQ Q
uQ vQ
FQ Q
a
 






cc

(17)
since

 
22
max 1
Q
uQ
uQ vQ

. Thus,
12 ,
uBuv
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.1079
is a continuous function and 12 :()()B . Ana-
logously we show that 22 :()()B
.
Consider corresponding to (13) linear homogeneous
equation

 
,, dcuQKQQuQ Q



. (18)
Above it is shown that the integral operator in the right
part of (18) is self-adjoint and positively determined.
Hence, its eigenvalues are real and nonnegative [9].
From here follows that cannot be eigenvalue of (18).
Then this equation has only zero solution uQ()0
.
Thus it is shown that necessary and sufficient condition
for existence of inverse operator is satis-

1
1
11
IB
fied [11]. Since 2111 , then BB

1
1
21
IB
exists
too. Easily to show [12] that



2
1
1
11
11
11
11 11
,0
,
sup 1
,
uLu
IB
IBuIBu
q
uu






.
From here follows, that is a limited
operator.
1
1
11
IB
Using existence and limitations of the operators
and

1
1
IB
11
1
1
21
IB

11
v I



w
12
22
,
.
(19)
e write (13) in the form





1
111
1
11
221
,,
,,
uBuB Buv
vBuvIB Buv



Theorem 1. The operator determined

12
,BT
BB
by (19) maps a closed convex sanach space et SM of the B
() in itself and it is completely continuous.
Proof. Before it was shown that :()B().
To prove the property of completee continuity of th
operator

12
,BT
BB it is necessary to prove its com-
pactness y [7]. We consider each of opera-and continuit
tors

1,Buv and
2,Buv in a system of Equations
(19) aduct ofmited (continuous) and non- s the pro linear li
linear operators. Since

1
1
IB
,

1
1
IB
11 21
are limited operators, then for complete continuity of the
operator

12
,BT
BB it is sufficient to show complete
continuitys of operator
12 ,Buv
, 22 (,)Buv. We shall
show it on the example
12 ,v
.
Bu
Let

111
,T
f
uv and,

T
222
f
uv be arbitrary fun-
ctions belonging to
S, and or 10v. It is
10u
necessary to show, that

12 1C
Bf Bf
12 20
s a

12 0ff. Let us
assume
v2 = v1 + Δv Takinain2
21
uu u,
g into account these equalities we obt
21
uu
u
22 2 2
22
221 1
11 22
11
22
1
uvuuvv uv
uv uv
 

At
.

0
C
u
,

0
C
v
we have:

12
22 22
0,
1122
0
1
22
0,
11
0
22
11
22
11
22
22 11
11 22
11
lim
lim max
1
1
22
1
0,
22
1


 







 






u
v
uQ
v
uu
uvuv
u
uv
uu vvuv
uv
u
uu vvuv
uv uv
(20)
since
22
11
22
0, 11
0
22
lim max11
uQ
v
uu vvuv
uv
 


 



.
Analogously we obtain
12
22 22
0,
11 22
0
lim max0
uQ
v
vv
uv uv
 



. (21)
Thus, from equalities (20) and (21) follows

 

 

 
121 11222
0,
0
0,
0
12
22 22
11 22
lim max,,
d0
u
v
uQ
v
FQ KQQ
uQu QQ
uQ vQuQ vQ


 






lim ,,Buv Buv


 



 c
.
Analogously


()
()
221 12222
0,
0
lim ,,0
C
C
u
v
BuvBuv


.
Therefore, is a continuous operator
fro

12
,BT
BB
m
into
.
Sho a setunw that of fctions satisfies
12wM
SBS
2Further for reduction of notations the dependence of functions u1, u2,
Δu, Δv on the variable Q is omitted in (22) and (23) . co[5], that is nditions of the Arzela Theorem we show
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.
1080
that functions of a set w
S are uniformly bounded and
equapotentially continuoLet

12 ,wB uv, where us.

,T
f
uv is an arbitrary function of a set
S. Then
for

12
,QQ ,QQ


analogously w(17) with e
have
 
12 dwQwQFQQ
a


 .
Thus the functions of a set are equapoten-
12wM
SBS
tially continuous.
Uniform boundedness of a set follows
fr
12wM
SBS
om inequality

 
 
  
22
22
max,,d
()
max,,d,
Q
Q
uQ
FQ KQQ Q
uQ vQ
uQ
w
F
QKQQQM
uQ vQ


 

 




c
c
(22)
where (,)
T
f
uv is an arbitrary function of a set SM.
Thusr 1
B is completely continuous in the the operato
first equation of system (19). Complete continuity of
operator 2
B is proved analogously.
Let ,)
T
(
f
uv be an arbitrary function of a set S
an
M
d ( ,)
T
,) (
T
g
huBv. Show that the function (,)
T
g
h
belongs to a set
S. Using the inequalities
A
xAx a

nd 1
11IB q

11 we have
 

 
1
1
1
11
() (,)
.
CCC
C
CC
gQB uv
I
Bw

 


qM
Analogously we obtain:

  

 
2
1
1
21
(,)hQB uv
.
CC
C
C
CC
I
BqM

 
 

From these inequalities follows that B
M
M
SS
tely contin
. So,
the operator

12
,BT
BB is compleuous
mapping the cloet sed convex s()
M
S into itself.
The theorem is proved.
As a corollary of Theorem 1 satisfaction of the
Schauder principle conditions [7] in accordance to which
the operator

12
,BT
BB has a fixed point

,T
f
uv

to a set , belonging
S, foll
(13) and, respectively). Substituting

,T
ows. This
point solves , (6
f
uv

into (10), we obtain the solution of (5),
tionary point of functional (4).
Concerning the synthesis problems of lin
which is a sta
ear radiator
for the case of one-dimensional domains the solu-
tions of system of equations similar to (13)re investi-
gated, in particular, in [13]. The obtained there results
show that nonuniquness and branching of solutions, de-
pendent on the size of physical parameters of the prob-
lem are characteristic for special case of equations of
type (13) (when variables are separated). The results [13]
can not be transferred directly to two-dimensional
nonlinear integral equations of type (7). Here unlike the
branching points [13] there exist branching lines of solu-
tions, and the problem of finding the branching lines is
not enough investigated nonlinear two-parameter spectral
problem.
a
. Equations of a Set of Branching Points
the case when the kernel of (7) determined by (8) is
3
In
real, (7) in a space of real continuous functions
C
has the form

 

,, d
,,sign d.




KQQfQ QfQ
F
QKQQfQ Q
c
c
(23)
Assuming in (23)
sign 1fQ
tegral linear
we obtain the sec-
ond kind Fredholm inequation with sym-
metric and even kernel
 
1,, dc
f
QKQQ
 fQQQ

F. (24)
Here the right part

1
Q

F,,dcFQKQQQ

is a nonnegative function. It was shown that correspond-
ing to (24) homogeneous Equation (18) has only zero
solution. From here follows that (24) has unique solution
0()
f
Q, belonging to the space ()C and
0( )1Qsign f
, that is solution 0()
f
Q is nonnegative.
Further welution l shall call the so0(,)fQc as initia
so tion lution of (7). Corresponding to it solu

00
,,,ccuQ fQ

0,0cvQ
we shall call as initial solution of a system of Equa-
tions (13).
To find the branching lines and complex solutions of
(7), which branch-off from the real solution
0,cfQ
we consider the problem on finding such a sees t of valu
of parameters

000
12
,ccc and all distinct from
,cfQ solutioh satisfy the conditions ns of (13), whic
0



0
max ,,0,ccuQfQ


max ,0,
c
Q
QvQ


(25)
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.1081
as

00cc. Conditions (25) mean that it is necessary
to find small continuous solutions in



0
,, ,cc cwQuQf Q ,
0

,,ccQvQ
,
converging uniformly to zero as c
is necessary also to take into accou

0
c
nt th
. In addition, it
e direction of
convergence of vector to
Put
c

0
c.

00
112 2
, ccc c

  (26)
and we shall find the deired sotioslun in the form



0
0
,, ,
,
 
,,
,.
(27)

vQ Qc
uQf QwQcc
Further we omit the dependence of functions

,,wQ
and

,,Q

on parameters
and
for reduction of notations.
Present some properties of integrands in (13). They are
co
and (27) it i-
r series with respect to the
fu
ntinuous functions of arguments. We substitute (26)
n (13). Then inegrands expand in the un
formly convergence powe
nctional arguments w,
and numerical parameters
,
in the neighborhood of point
 


00
0
,,,0ccfQ :

 


 
22
0
0
,, uQ
KQ
QuQ Q



 
c
,, ,
mnpq
mnpq
mn pq
F
Q vQ
AQQwQ Q




c
u




 
22
0
1
,,
,, .
mnp
mnpq
mn pq
vQ
KQQvQ FQ
uQ vQ
BQQwQ Qq




 


c
c
(28)
Here ,
are c
ficientsi on argu-
ments. Su
, we obtain a


0
,,c
mnpq
AQQ
of expansion cont
bstituting (28) in


0 as a solu
f nonlinear equation

0
,,c
mnpq
BQQ
nuously dependent
(13) and considering
tion of this system
s with respect to
oef-
0
stem osmall solu-
tions w and
,cfQ
sy
:


 









 
0
0
0
0
2
1,,d
,
,, d,
pqm n
mnpq
mn pq
Q
QFQKQQQ
fQ
BQQwQ QQ

 






c
c
c
(30)
where







00
10 0010
00
01 0001
,,,
,,,



aQA QQQ
aQAQQQ
cc
cc
d,
d.
Extracting in a system of Equations (29), (30) the lin-
ear members for and w
, to find a set of branc
f the so
hing




 
0
00
,, d
,


10 01
0
2
,
2π
,, d,
 




pqm n
mnpq
mn pq
wQ
a aQ
K QQwQQ
cQ
A
QQw QQQ
c
c
(29)
c
c
points olution
0c
al equtions
,fQ
a
we have an integ
f linear inr
rated
system oteg

1,, dcwQK QQwQQ

 
, (31)





1
0
0
,,,d.
,
 

 Q
Q
F
QfQ KQQQ
fQ
cc
c
(32)
We shall call a set of values of parameter
 
000
12
,ccc
neous Equations
tions as a set of
solution
, at which the system of linear
(31), (32) has distinct from zero
points of possible branching of initial
homoge-
solu-
0,cfQ
. Note that the system (31), (32) is
ely the functions and noncoherent relativ w
. Prev
hown that equatiof ty31) has
i-
ously it has been son pe (
only a zero solution. Therefore the premndiobl of fing a
set
of branching points under condition
0
fQ,c
0, is
reduced to equation
 



1
0
0
,,, d,
,




QT
Q
F
QfQ KQQQ
fQ
c
cc
c
(33)
that is to a nonlinear two-dimensional spectral problem
[14,15]. The eigenvalues of this equatio of n form a set
points of possible branching of solutions of a system of
nonlinear Equations (29), (30). Corresponding eigen-
functions are used to construct the branching-off sol-u
tions of equations [16].
Note, that construction and justification of conver-
gence of numerical algorithms to solve the nonlinear
two-parametric spectral problem on eigenvalues (33) it is
necessary to solve the corresponding auxiliary one-pa-
rameter nonlinear spectral problem [14]. In this connec-
tion at first we consider two-parameter nonlinear spectral
problem on the general (operational) level in the Banach
spaces.
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.
1082
Nonlinear Spectral 4. Two-Dimensional
Problem
4.1. Statement of the Problem. Existence
Conditions of Descrete Spectrum of
Operator-Function
Note that different approaches are used to discretization
of the original problems [7,14] at construction of the
numerical algorithms to find the solutions of various
typr spectral problems. That is to say that es of nonlinea
original problems in the Banach functional spaces E
are replaced by the corresponding problems in the fi-
nite- he
quesmate solutions of
iscretization problems totions of initial prob-
dimensional spaces n
E (n). In addition t
tion of convergence of
ex
approxi
act solud
lems, whenever dim n
E, n is important,
since the input and approximated equations are consid-
ered in various spaces.
Let E be a complex Banach space,

12
,
be
a vector parameter belonging to the domain
12
  (open connected set) of the complex space
2
. Here
ii
 ,

:
iiii
r

 
1, 2i, r be some real con-
stant. Consider the ctioperator-funon
,: ,EE AL
, which to each

12
,


as thsignse operator

12
,,EE

AL, where

,EEL is the space of bounded linear operators [7].
co
problem of
Let usnsider the nonlinear two-parameter spectral
the form

12
,0x

A, (34)
in which it is necessary to find the eigenvalues


00
,


12 to them eigen-and corresponding
vectors (0)
x
E(0)
(x

00
12
,

0) such that


0
0x
A.
In pan rticular, in view of (33), the operator-functio

12
,
is represented as

12
,T

A
A

12
,:I

L,EE. (35)
Here

12
,T
is a linear completely contin
erator acti
uous op-
the Bang innach space

EC and ana-
t on two-dimensional parameter

12
,
lyticallyn depende
,
I
is a un
Banach s
ique .
paces and also
th
operator in
Let the E, E

E
n
n
e system ()
nn
p
P of linear bounded operators
n
E such that
1, 2,
:
n
pE
,,
n
nE E
pxxnx E (36)
be. Operato
bo
givenrs n
p are called conjunctive opera-
tors [7,14]. From the principle of uniformundedness
[14] for p the inequality follows
n

const
n
pn.
very space E the elemLet in enn
x
ent be selected.
Writing these elements in order to increase the numbers
we shall form the sequence

n
x
.
her approachUsing eit scretizaton of ori
problem the operator-function
to diiginal

,EE is ,: AL
approximated, respectly, by the approximate opera-
tor-functions
ive

,: ,nn
EE 
n
AL, n. As a re-
sult, at each
12
,

we obtain a sequence of
operators (,)
nnn
EE
AL which convergences to opera-
tor (, )EE
AL at satisfaction of theorresponding
conditions.
Definition of various type convergence of opera-
tors
c
s of
m (33)if
In particular,
described by (3
disc
n
A to A is given, in particular, in [14].
Discretization of original proble, choce o the
spaces n
E and determination of operators :
nn
pE E
are realized in various ways. the opera-
tor-function is5) and E is the separable
(infinite-dimensional) Hilbertian space, one of the ap-
proaches toretization (34) consists in the following.
Consider an arbitrary complete orthonormal in E sys-
tem
if
of functions

1
kk
x
. Each element
x
E can be
presened as series t
1
kk
k
x
cx
where
,xx
kk
the Four coefficient of element
c is
rie
x
. If T
12
,
is a
ta
linear continuous operator, acting in the separable Hil-
bertian space it admits matrix represention [9]:
 

1212 ,1
,,
Mjk
j
k
Tt
 
, (37)
where
12 12
,,,
j
kkj
tTxx

. In addition a se-
quence of the Fourier coefficients lement of e
12
,
y
Tx
is obtaia sequencerier ned from of the Fou
coefficients of element
x
as a result of multiplication
of the matrix 12
(,)
M
T
by coefficients ot f elemen
x
.
Using the matrix representation of operator
12
,
M
T
the spectral problem (34) is formulated as

12 12
,,
MMM
xT Ix
 
0
A
IM is a unit matrix in the s
, (38)
where pace of sequences
2
l.Thus, the operators ()T
and )
M
T( are equiva-
lent in the sense that they to the same element
x
E
assign one and the same element
y
E. But we obtain
the Fourier coefficients of element

y
x as a result
of action of or

T on the element the operatM
x
.
Os coincide,bviously, that eigenvalues of these operator
that is the spectral problems (34) and (38) are equivalent.
In this case we put that the finite dimensional spaces n
E
are generated by the bases

1
kk
x (n) and to each
n
element
x
E
the operators :
nn
pE E assign the
element
1
n
kk
k
x
cx
where

,
kk
cxx. As a ,
operator
result
n
M
T approximated to s described

M
T i
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.1083
rix-fuby the finite-dimensional matnction
 
1212 ,1
,,
n
n
Mjk
j
k
Tt

. (39)
Apply other methods of discretization to (34), in par-
ticular, the quadrature (cubproce for the case ature) sses
of homogs integral equationge of deri-eneouns and cha
vates by tnce analogfferential equa-heir differeues in di
tions. Weroximate o find approxi- obtain appproblems t
mate the lues and eigenvectorsmatrix opera-eigenva of
tor-functions in the form

12
,0,
nn
xn


A.
Moreover, the problem of determination the eigenval-
ue
(41)
If
(40)
s is reduced to finding the roots of the determinant of
n-th order that is the roots of equation

 
 
12
111 2121 211 2
211 22212212
,
,, ,
,, ,
det

 
 



 
n
n
n
aa a
aa a
 
0
,, ,
 


 

1122 1212

nn nn
aa a
n

12
,
n
A has form of (35), then
,
.
k
k
Note if the coefficients
 

,12
,12
,12
,,
,,1,
jk
jk
jk
tj
atj

 


12
,
ij
a
arguments, the
are continuously
differentiable functions of partial deriva-
tives

12
,
nj

 (j1, 2)
vation [17].
are determined by the
rules of determinant deri
der the auxiliary eter s
tral problem, necial case of (34).
Assume that variable
Consi nonlinear one-param
cessary later on, as a spe
pec-
2
in the operator-function
12
,
A
ated function
is expressed ome one-valued fferenti-by sdi
21
z
mapping the subdomain
omain
1, 1
 into some subd2,2
. In the
simplest case we put 21

( is some real pa-
rametenoperatunction


111
,z
r). Itroduce the or-f

AA for 11,
, which is reduction
of the operator-function
12
,
A. We shall consider
one-dimensional spectral problem
10x
(42)
A
in which we assign to each value

11
,z


the operator



11
,,zEE

AL. Analogously to
(40) we consider a approximate sequence of discrete
problem of (42)

1
,0 z n (43)
Denote the spectrum of operator-function

,1 ,
nn
x

A
1
A as

s
A. Assume that

1,
s
A.
For the spectrum
sAof the prob
w
lem (34) the fol-
lowing theorem is valid.
Theorem 2. Let the folloing conditions be satisfied:
1) operator-function

,: ,EE AL is holo-
morphic, and
s
A;
2) operator-functions

,:EE AL

,
n
y closed bounded s
nn
et 0
are
holomorphic and for an

the following inequality
12
x ,
nc

0
ma

Aconst
()n is valid;
3) operators
 
12
,,EE
AL
,
,,
n
EE

AL
()
12 nn
n
are the Fredholm op-
erators with zero index for any
12
,


;
4) spectrum
1,
s
A of func-
tions
and a sequence
12n,
are differentiable in the domain
;
5)
nAA
is stable for any
\rsAA
.
Then the following statements are true:
1) every point of spectrum


0
1s
A

is isolated, it
is perator eigenvalue of the o

111
,z

,AA the
finite-dimensional eigubspa
c
ensce



0
1
N
A and the
finite-dimensional root subspace t; orrespond to i
2) for each

0
1s
A there exists a sequence

0
1,n

,n
s
A 0
()nn, s
0
n
1,
from uch that

00
1, 1
n
;
3) each point
 

000
,
11
z

is a spectrum
int of the operator-function
12
,
A; po
4) if in some 0
- neighborhood of the point
 
000
11
,
z



12
2
,0
nz


, then in
anll arbitrarily sma
-neigh
exists a contiuous differenti uncti
borhood of that point there
nable fon
2, 1

, 1), that is i

bicylindric d
which is solution of (4n some
omain al

 
0
012011 2
,:
0
12 2
,

 


th m of the
operator-function
ere exists a connected component of spectru
2
,
N (1
,2
1
A are small real
constants).
ple
te spectr
Proof. The proof of Theorem is based on Theorems 1,
2 [14, p. 68, 69] and on existence of implicit functions
(see, exam, [18]). At first we show that the conditions
of Theorem 1 [14, p. 68] concerning the existence of
discreum of operator-function

1
A
rem.
follow
from the conditions of formulated Theo Under the
conditions of Theorem the operator

12
,
A is Fred-
holm operator with zero index for each

12
,


,
and the operator-fu
 
,: ,EE is holo-
mo Fro
nction

AL
rphic. m here follows that at each 11,
the
operator
1
A, as reduction of the operator
12
,
A,
is also Fredholm operator with zero index, and the op-
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.
1084
erator-function
 
11,
:,EE

AL is holomorphic.
So, for the operator-function

1
A the conditions of
Theorem 1 [14, p. 68] are satisfied, from which follows:
each point

0
1()s
A is isolated, it is the eigenvalue
of the operator 1
()
A, the finite-dal eigen-
subspace and finite root subspace corres,
each point

00
11
,z


is thespectrum
point of thtor-function
im
p


0
ra
ension
ond to it. Thus
e ope
12
,
A.
In addition, the conditions of Theorem 2 [14, p. 69]
are satisfied for the operator-function
11,
:,EE

AL. From this t follows: at
n larger than some 0n for each

heorem
0
1s
A
there exists a sequence1,n

from

1, ,nn
s
A
such that

0
1, 1
n
. Thus, each point

(0)(0)
12
,

 


00
11
,z

is the eigenvalue of operator-function
11,
:

Atively, the eigen-,EEL and, respec
value of operator-function
,: 
nn
ence
,EE .
n.
AL


0
Since
(44)
1, ,
nn
s
Ais the root of (41), then from here follows that
 


00
1, 1,
,0,
n
z


From the converg of sequence

0s
A to


0s
1, ,
nn
1
A follows arbitr that for anarily small num-
ber 0
there existsber such num0
Nn that
 
00
1, N1



00
1, 1,
,0
NNN
z


and 
.
Let 1,
2
be independent variables in the domain
, and



0 0
121 1
z
be a spectrum
operator-function
00
,,
 

point of the
12
,
A belonging to


ss
AA
functions
. Under the conditions of Theorem the
12
,
n
are differentiable
z
bo
in
and
the neigh-
rhood of the point



000
12 1
,
 


0
1
,

0
N



0
1,
,0
N
z

. In addition tt
1,
2
Nh
0gs to
e poin


0
1, 1,
,
NN
z


belon
-vicinity o
. According to the Theorem ab
of poi
1
f thet
ere ex
poin

0



0
12
,out implicit


00
function in some neighborhoodnt 12
,
th ists the continuous differentiable function
2N




quation

12
,0
N

,
and

1, 1,
nN
z

tenc
, solving the e


00
N
. From here fo
pectrum component of the
llows exise
of connected sor-func-
tion
operat
,:A,EEL

in some bicylindrical domain



00
012
,
0111222
: ,

 ,
where 1
ε, 2
are small real constants.
oved. Theorem is pr
Comment. Note that in the case of real para1
meters
and 2
the presence of a singular point in the equation
12
,

0
[19] is one of the sus fficient criterionof
action of condition
sA. The point satisf

00
12
,

is a singular point of the curve which is
prese

,0

nted by the equation 12
when
 
 
00
12
1
,


0
,
00
12
,


d the second
2
0
, an
orre nonzero: der partial derivatives a
 



00
2
00
212
12 ,
,0, 0,




22
12

00
2
12
,

12
0

()

.


These derivatives and tr derivatihe third-ordeves are
continuous in the neighborhood of the point

00
12
,

. If in addition
 
 
 

2
0000
22
12 12
,,
 

 

00
2
12
22
12 12
,
0

 


 


,
then the point

00
12
,

is the second ordeot of r ro
equation 12
(,) 0. Inside of a sufficiently small
ra

00
dius circle with center at point

12
,

the left part
of equation 12
(,) 0
becomes zero only at point
(0)(0)
12
(,) (0) (0)
12
(
,)
is the i
, i.e.
solated point of spectrum.
4.2. Finding the Connected Components of a
Spectrum
the exiThus, assumingstence of discrete spectrum
1,
s
A
robl
and solvi
em (42), set of the eigenv
ng an auxiliary one-dimensional
spectral pwe find a alues
 
000
,
11
z

, whichalso to the belongs
perator-funcspectrum of otion

,: ,EE AL. To
find the ccted comonneponents of a spectrum in some
neighborhoods of the points
 

000
11
,z 
consider thewe problem on finding the solutions of
quation e
12
,0
n

, as the problem on finding the
implicitly given function

221

at satisfaction of
 
condition
00
12 2
,0
n
 
 (or
112

at
 

00
satisfaction of condition 121
,0
n
 
), solv-
ing the corresponding Cauchy problem
 

 

00
12 1
2,
dn
00
2
,
112
dn




, (45)
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.1085
ne-di
orm
0
n
. (47)
alues of this problem
n
. (48)
Solving the problem (45), (46) in some neig
of the point
co




00
1 1
z
 
. (46)
Corresponding (38) auxiliary omensional spectral
s the f
2
problem ha


nn
Obviously, the eigenvare the





11 11
,,
nn
MMM
zxT zIx

A
roots of equation
 


111
det,0
nn
MM M
Tz I

 
hborhood
 


12
,
iii
z

, we find the i-th
nnected component of spectrum of the operator-func-
tion

12
,
n
M
A.
Return to finding the solutions of (33), in which
are real spectral parameters. Let
c,
1
2
c

12
,
c, cc
12
ccc
 , where
:0
ii
cicic
ccr . By
direct check we set that for arbitrary values of parameters

12
,c
cc the func
isnctions, where
f (7). Write the neces
tion
 
,,ccQfQ
, (
00
one of the eigenfu
is the ini-
49)
,cfQ
sa
0
tial solution ory in what follows
equation
 
 



0,,,
,
 Q
0
d
QT
F
QfQKQQfQ
ccQ
c
c
0 (5 )
conjugate with (33). For arbitrary

12
,
c
cc the
fu

nction
0
 
0
,,ccQFQfQ

(51)
is one of the eigenfunctions of (33).
The existence of distinct from identical to zero solu-
tions of (33) for arbitrary
,cc indicates that
there i
12 c
nt of spectr
he condition
. To satisfy th
, (51) from th
s a connected componeum, coinciding
with the domain. So, tof Theorem 2:
is nois condit
genfunct (49)e kernel of in-
on
c
t satisfied
ions

c
sA
exclude ei
ion we
tegral equation (33). Consider the equati
 
,,,ccc
QT QQ
 


KdQQ
 , (52)
where

 

0
0
00
00
,, ,,
,
,,
QQK QQ
fQ
QQ



cc
cc
K
. (53)
From the Schmidt Lemma [16, p. 132] follows that
1
,FQ fQ

c
c
is not characteristic value of (52) for any value

,cc , that is

is not an eigenfun
12
equation.
0,cQ
eby the conne
n c
cluded from
ction of this
Ther cted component
domaiand corresponding to the function
is ex the spectrum of operator.
coinciding
with th
0,cQ
e
Using (8) we are sure that for the kernel of operator
c
T is fulfilled the inequality




 

0
3
12
22 2
0
2
2
12
0
2
d
,
2π
,d .
2π
Q
Q
cc QQ







2
22
,, dd
,
1
QQQQ
Q
cc








c
c
 c
c
K
Here
is the measure of the domain
. From
e obtained inequality follows that

c
T is the Fred-th
holm[20]. Moreover, it is a operator with zero index
completely continuous operator in space
2
L [21].
Functions entering in the kernel of thr (35), e operato
admit the analytic continuation into the complex domain
c, if and are assumed as complex parameters.
1
c2
c
Holomhy ofrator-function orp ope
12
,cc A
,c
12
Tc I llows [14] from existence of partial fo
deries vativ12
,ccA
i
c
1, 2i at arbitrary pot in

00
12
,
c
cc owing to continuity ofkernel the
,,c
QQ
K according to a set of their variables in the
domain
c
 and existence and continuity of
partial drivative es
12
,
i
cc
c
K
1, 2i, what is easy to
verify.
52), 21
cc
, we shall consider the onPutting in (e-
dimensional o


 , (54)
spectral prblem
 
11
,, d
QTcuQQc QQ

K
G
where is

,, ,,,

QQ cQQcc

KK
. Since

Tc
111 1
f the operator ()Tc
, from here follows that reduction o

Tc is tholm operator with zero index for ane Fredhy
1
11,
c
, and the operator-function



1
:,IEE
L
is holomorphic.
T
A
If
1
s
A, from holomorphy of operator-function
and from the Fredholm property of the kernel
111
,, ,,,
QQ cQQcc

KK satisfaction of the con-
ditions of Theorem 2 follows. In accordance with this
Theorem every point


0
cs is i it is
1solated and the
A
eigenv


00
alue of (54). Respectively, the points 12
,cc
 
0
1
c
are eigenvalues of (54
0
1
,c
). To find the spec-
trum connected components (s of 52) in the vicinitie
points
(0) (0)
12
,cc we solve the Cauchy problem (45)
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.
1086
an46), usingd ( the found solutions of auxiliary problem
(54) as initial conditions.
ically the ei-
iary problem
(43). Consider
4.3. Numerical Finding the Eigenvalues of the
Problem
We shall construct algorithms to find numer
genvalues of (54) what corresponds to auxil
some convergent cubature process [14]



1
d,
n
jn jnn
j
xQQa xQxn

 (55)
with coefficients
jn
a and nodes jn
Q
(1jn). We reject the remainder term

n
x
in (55)
nd replace integral in (52a) by it. Giving the variable
in thsional spaces
Q
us values in
QQ (1in), we have the homogeneo
system of linear algebraic equations concerning
,u:
1,
nnn
u



11
1
,,, 1
n
n
inMnjnin jnjn
j
uTcuaQQcuin
 
K(56)
where

uuQ. Solving the eigenvalue problem (56)
in in
e finite-dimen

n
EC,
n
w
approxialues, convergent to exact solutions
as
Finding , in
These stions of equation we denote as .
Return to two-dimensional spectral prob
plying the (55) to (52), we obtain a system of lin
ns similar to
,
0
n
(59)
we consider as a problem on finding the impl
fu chylem
(4
e find
mate eigenv
of the problem (54).
the eigenvalues of (56) is reduced particu-
lar, to finding the roots of equation
 
11
det 0
n
nMn
cTcI
. (57)
olu
n

1
i
c
lem (52). Ap-
ear
equatio (56)


12 12
1
,,
n
n
inMjnin jnjn
j
uTcc uaQu

K
(58)

,
1.
Q cc
in
Finding the solutions of equations
 

12 12
,det ,
n
nM
ccT ccI 
icitly given
nction

221
ccc, reducing it to the Cau prob
5), (46). Since to each isolated root of this equation
corresponds eigenvalue
 


nditions


121 1
,,
iii i
ccc c
of prob-
lem (58) we use solutions of (57) as the initial co
(46). Thus, we determine the initial conditions (46) for
the Cauchy problem as . If
 


211
iii
ccc

12 2
,0
ncc c then solving the problem (45) (46)
in the differentiable each vicinity of points

1
i
c, we find
function
21i
cc
which satisfies the condition



1
ii
cc
In the case, when

11
,
ii
cc
is of a real eigenvalue
the problem (57),
21i
cc
are real differentiable
functions describing in the vicinity of points
 
11
,
ii
cc
some smooth curves. Tse thhat is, in this cae equations
(52) and (33) have a linear spectrum, respectively.
Thus, solving the proble (57) and (58), we find a setms
of values of parameters
c at which the bran-
12 c
,c
ching of ctions of Equation (7) from the real omplex solu
initial solution
0
f,cQ at 0
, 0
is possible.
U
Functional has smon branching- aller values
ofhe solution
xamples
f solutions than on t

,cfQ .
5. Algorithm of Finding the Solutions of
Nonlinear Equation. Numerical E
0
Present one of iterative processes for numerical finding
the solutions of system (13), based on the successive
approximations method:


1
11


12
122
,, 0,1,.
nn
n
vI
BBuvn


1
11
1112
1
,,
nnn
uIBBuv



(60)
Before it was shown that the inverse operators

1
1

.
1
11
IB
ited. and

21
IB
exist and are lim
1
1
In the case of even on both arguments function
,
F
12
ss and symmetric domains G and
at exe-
cution of iterative process (60) it is appropriate to use the
invariance property of the integral operators B1(u,v) and
B2(u,v) in the system (13) concerning the type of parity
of functions u(s1,s2), v(s1,s2). Functions and hav-
ing some type of parity on the correspng am
belong to the invariant sets and of
u
ondi
kl
V
v
rgu
the s
ent
pace
ij
U
()C
where the indices taes 0 1. In
pa
,,,klij ke valu or
rticular, if
12 01
,us sU then
12
,uss
,
12
,uss

12
,us s. By the
1
s
2
,us
direct check wone are ct there are such inclu-vinced tha
sions:


12
,,
B


ij klijijklkl
ij klij kl
BUVUBUVV
UV UV

(61)
From these relations, in particular, follows the possi-
bility of existence of fixed points of operator B be-
longing to the corresponding invariant set, that is to solu-
tions of (13) and, respectively,). (7
Substitute into (10) the function

arg n
fQ
arctg nn
vQuQ f succes- obtained on the basis o
sive approximations (60). As a result we have a sequence
of function values which we denote as {Un}. For this
sequence the Theorem 4.3.2 and corollary 4.3.1 [4], and
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.1087
the Theorem 4 from [22] are valid. From here follows
that the sequence {Un} is relaxation for functional (7)
and the numerical sequence

n
U
is convergent.
Consider the numerical examples of approximation of
even on both arguments function
 
121 2
,sinπssinπsFss (Figure 1) in the domain


12 12
,: 1,1ssss .
In Figure 2 in logarithmic scale the values of func-
tional

U
, which it takes on different types of solu-
tions of system of (13) at change of the parameters
12
,cc on the beams 21
0.8cc are presented. The
curve 1 corresponds to the initial solution

012
,
f
ss .
The curve 2 is a branching-off solution at point
 


o
11
, 2.345,1.876cc with the prrty
12 pe
 
12 1
arg ,arg ,
2
f
ss fsshe analysis of . From t
Figure 1. The function
 
1212
,sinπssinπsFss
given in the domain
:
12 12
,1,ssss.1
F
Figure follows that branching-off solutions at point
 
11
12
,cc are more effective compared with initial solu-
igure 2. The values of functional on initial and branching-
off solutions.
tion , since the functional
0
f
U
accepts smaller
valu branching-off solution initial. es onns than o
The points of possible branching of solutions of (7)
(spectral lines of (33)) for given
1212
,sinπssinπsFss are shown in Figure 3.

12
,
f
ssFigures 4 and 5 present and
12
arg ,
f
ss
of approximate function corresponding to the branch-
ing-off solution of system of Equations (13) at с1 = 8 and
с2 = 6.4.
Correspoding to this solution the functions
,Uxy
and
arg ,Uxy of the Fourier integral prototype in a
spatial image and image by the level lines are shown,
respectively, in Figures 6 and 7.
Figure 3. Points of possible branching of solutions (spectral
lines) for given

1212
,sinπssinπsFss .
Figure 4. The modulus of approximation function.
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.
1088
Figure 5. The argument of approximation function.
Figure 6. The amplitude of Fouier integral prototype.
Figure 7. The argument of Fouier integral prototype.
,Uxy
e domain
As we see in these figures, the function is a
nonsymmetric relatively to the center of th
along the axis , and accepts the
0 or in thondins of the dom
, t is funct
G
value
ain
OX
e corresp
ion

arg ,Uxy
ing subdomaπ
hat
G
,Uxy is real.
that the
Thus, from
given symme
function
the
tric analysis of Figures follows
12
,
F
ss (even on both arguments) on the
beam 21
0.8cc
at is approximated effec-
tively btimce of nonsymmetrical by
modulntegypes, that is the functions

1
11
cc
al choi
ral protot
y the op
us Fourier i
,.y Ux
6. To Selection of Parameter
We shall present some argumentations concerning the
choice of the weight parameter of regularization
in
the optimization criteria (4). Many of works (see, [23-26 ])
areof
soly for l
devoted to this question. Efficient algorithms
lving this problem are developed maininear
operator equations of the type
LuF
(62)
with approximate right part
F
, in which a priori the
ror er
is known. Thiled definition is given in eir deta
[23,25]. The principle of residual is the most applicable
one in practice. Here we choose such number
for
which acy the equality with the necessary accur
LuF
 (63)
is execu is a minimum point of smoothing func-uted (
tional defid on U
H
ne ) dependent on the parameter
.
As shown in [1], the principle of residual (63) to deter-
mine the parameter
in the case of nonlinear operator
L can be applied when L is a convex operator. Gen-
erally, the residual (63) may be discontinuous or on-n
monotonous function with respect to parameter
.
Therefore Equation (62) can not have any solution or
have a set of solutions.
The error
is unknown a priori, as a rule, in the
problems of nonlinear approximation. Decrease of pa-
rameter
in the functional (U) reduces the require-σα
ments to the norm U. As a result, the norm of the
Fourier integral prototype minimizing the functional
σα(U), inversely depend on
. At reduction
the
accuracy of approximation in the limits of the dain om
, as rule, increases, but the value of function
12
,fss outside this domain increases also.
At concrete calculating the parameter
can be se-
lected on the basis of some physical argumentations ad
numerical experiments. In particular, in the antenna syn-
thesis problems the rameter
n
pa
can be selected from
e satisfaction of equal engy condition [4] ther
 
2
2
22
UF
. (64)
L
LG
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.1089
(A numerical example of dependence of solutions of7)
on the value of parameter at approximation of the
function

1
12 2
c
ossinπ
2
πs
,
F
ss s is the proof of the
above presented arguments. In Figure 8 are given the
values oapproximate function

f 12
,fss in the sec-
tion 10s. From the analysis of the Figure, we see that
the quality of approximation of the given function on the
interval 2
11s  increases hen parameter w
de-
creases, while

2
0,fs increases outside this interval.
7.
the modulus of double Fourier transform
sm
i
method of solving the tw
nlinear
i s
ase of even by both arguments (one argument) function
Conclusions
Note the main results and problems arising at investiga-
tions of the considered class of problems:
1) The method of nonlinear approximation of finite
nonnegative functions with respect to two variables by
with use the
oothing functionals is developed in the work.
2) It is shown that non-unqueness and branching of
solutions is characteristic for this class of problems. The
numericalo-parametric nonlin-
ear spectral problem enabling to find the branching lines
of solutions of Hammerstein type no two-dimen-
sional integral Equation (7) is proposed to study the
non-uniqueness of solutions dependent on the value of
parameters ,cc entering the Fourier integral.
3) At fsolutions of system of Equation (13)
12
nding the
by the successive approximations method (60) in the
c

12
,
F
ss to obtain
ecessary to select th
the solution of concrete type it is
e initial approximation belonging to
n
the corresponding invariant set of nonlinear operators
Figure 8. The modulus of approximate function

2
1
12
π
,cossinπ
2
s
F
ss s in the section 20s correspond-
ing to various regularization parameters
.
1
B,
4)
2
B
Inve
(61).
stigations of branching of existing solutions de-
pendent on physical parameters entering the Fou-
rier integral are the main difficulving this class of
problems. As follows from the ted researches, in
particular, in [4,13], for a spec
12
,cc
lty at so
presen
ial case when
121 122
,
F
ssFsF s
tions with increase of pa
, the f existing solu-
significantly
quantity o
rameters 12
,cc
increases. Note, that in many practical applications, par-
ticularly in the synthesis probleing systems, ms of radiat
obtaining the best approximativen function on to the gi
12
,
F
ss at concrete valuesters is of parame12
,cc
important. It allows to limit onestig of eself to invations
few first points (lines) of branching.
5) Obtaining the complete answer about exact qutity
of thpa-
dies.
[1]
.11008
an
e of existing solutions of (7) at concrete values
rameters ,cc are the subject of separate stu
12
8. References
A. N. Tikhonov and V. Y. Arsenin, “The Methods of
Solution of Incorrect Problems,” Nauka, Moscow, 1979.
[2] P. Savenko and M. Tkach, “Numerical Approximation of
Real Finite Nonnegative Function by the Modulus of De-
screte Fourier Transform,” Applied Mathematics, Vol. 1,
No. 1, 2010, pp. 65-75. doi:10.4236/am.2010
[3] E. G. Zelkin and S. I.
s and
Instid Ma
, “Elements of Func-
. VaiBran-
of Solutions of
.
in, “The Functional Analysis,” Nauka,
Solov’yev, “Methods of Synthesis
of Antennas: Phased Antenna Array Antennas with
Continuous Aperture,” Sovet radio, Moscow, 1980.
[4] P. O. Savenko, “Nonlinear Problems of Radiating Sys-
tems Synthesis (Theory and Methods of the Solution),”
tute for Applied Problems in Mechanics anthe-
matics, Lviv, 2002.
[5] A. N. Kolmogorov and S. V. Fomin
tions Theory and Functional Analysis,” Nauka, Moscow,
1968.
[6] М. Mnberg and V. А. Trenogin, “Theory of
ching Nonlinear Equations,” Nauka,
Moscow, 1969
] V. A. Trenog[7
Moscow, 1980.
[8] М. А. Krasnoselskii, G. М. Vainikko and P. P. Zabreiko,
“Approximate Solution of Operational Equations,” Nauka,
Moscow, 1969.
[9] L. V. Kantorovich and G. P. Akilov, “The Functional
Analysis,” Nauka, Moscow, 1977.
[10] I. I. Liashko, V. F. Yemel’ianov and A. K. Boyarchuk,
“Bases of Classical and Modern Mathematical Analysis,”
Vysshaya Shkola Publishres, Kyiv, 1988.
[11] S. G. Mikhlin, “The Direct Methods in Mathematical
Physics,” Gosudarstvennoje Izdatelstvo Tekhnicheskoy
Literatury, Moscow-Leningrad, Leningrad, Moscow,
1950.
[12] G. I. Marchuk, “The Methods of Calculus Mathematics,”
Copyright © 2011 SciRes. AM
P. SAVENKO ET AL.
Copyright © 2011 SciRes. AM
1090
avenko, “The Branching of Solutions of Antennas
sshykh Uchebnykh Zavedeniy Radioel
, “Analysis of Discretized Methods,”
mensional Nonlinear Spec-
oscow, 1965.
ekhniko-teoreticheskoje Izdata-
w, 1933.
lin, “Variational Methods in Mathematical
tics and Mathematical Physics,
eference Textbook,”
olving the
yi, V. V. Stepanov and
roblems in Reflexive
Nauka, Moscow, 1977.
[13] P. O. S [20]
Synthesis Problems According to the Given Amplitude
Directivity Pattern with Use of Regularization Function-
als,” Izvestija Vyek-P
tronica, Vol. 39, No. 2, 1996, pp. 35-50.
[14] G. M. Vainikko
Tartuskiy Gosudarstvennyy Universitet, Tartu, 1976.
[15] P. A. Savenko and L. P. Protsakh, “Implicit Function
Method in Solving a Two-di
tral Problem,” Russian Mathematics (Izv. VUZ), Vol. 51,
No. 11, 2007, pp. 40-43.
[16] М. M. Vainberg and V. А. Trenogin, “Theory of Bran-
ching of Solutions of Nonlinear Equations,” Nauka, Mos-
cow, 1969.
[17] I. G. Petrovskii, “Lectures on the Theory of Ordinary
Differential Equations,” Nauka, Moscow, 1970.
[18] V. I. Smirnov, “Course of High Mathematics, vol. 1,”
Nauka, M
[19] A. Gursa, “Course of Mathematical Analysis, Vol. 1, Part
1,” Gosudarstvennoje T
Spac
lelstvo, Leningrad, Mosco
P. P. Zabreiko, А. I. Koshelev and М. А. Krasnoselskii,
“Integral Equations,” Nauka, Moscow, 1968.
[21] S. G. Mikh
hysics,” Nauka, Moscow, 1970.
[22] P. A. Savenko, “Numerical Solution of a Class of
Nonlinear Problems in Synthesis of Radiating Systems,”
Computational Mathema
Vol. 40, No. 6, 2000, pp. 889-899.
[23] A. F. Verlan and V. S. Sizikov, “Integral Equations:
Methods, Algorithms, Programs. R
Naukova Dumka, Kyiv, 1986.
[24] V. A. Morozov, “Regularizing Methods of S
Incorrect Problems,” Nauka, Moscow, 1987.
[25] A. N. Tikhonov, A. V. Goncharsk
A. G. Yagola, “Regularizing Algoritms and a Priori In-
formation,” Nauka, Moscow, 1983.
[26] A. G. Yagola, “About Selection of Regularizing Para-
meter in the Solution of Incorrect P
es,” Journal of Computational Mathematics and
Mathematical Physics, Vol. 20, No. 3, 1980, pp. 586-596.