1. Introduction
In classical complex analysis, we have two different types of notations in the complex number set
. One is the Cartesian form (
), and the other one is the polar form
. Even though we have the Cartesian form, the polar form is needed depending on the situation. The Cartesian form is generally convenient, but if we have to use the angle such as in triangular functions, the polar form is better. Likewise, in fuzzy complex analysis
or
; see
Section 3), we can first consider the Cartesian complex fuzzy number form, but depending on the situation, it is necessary to define the polar form to express some special cases (see Example 2). Sometimes, the polar form in
or
is better than the Cartesian form. For example, if we want to express some situation with a “periodic” time series that has a fuzzy amplitude, the polar form is better than the Cartesian form. As we see in Example 2, we can express the periodicity easily if the data include the monthly property or the seasonality. However, due to the complexity of
or
, not all the properties in
hold in
or
Therefore, in this paper, we discuss similar properties in
that we can even have in
or
, and we also discuss some properties that we cannot have in
or
. For example, as we discuss in the paper, the complex fuzzy inner product does not exist based on the polar form. The Cauchy-Schwartz inequality holds using the Cartesian form in the complex fuzzy number set.
The definitions of complex fuzzy numbers have been introduced in several studies [
1,
2,
3]. The complex fuzzy numbers can be applied to many real applications [
3]. Buckley [
1] first introduced a complex number approach to fuzzy numbers, which was named “fuzzy complex numbers”. He defined the Cartesian form and the polar form of fuzzy complex numbers
z based on their membership function, which is a mapping from the complex numbers into
. On the other hand, Ramot et al. [
3] introduced a complex-valued grade of fuzzy membership functions to the magnitude (modulus) and argument of the polar form to define complex fuzzy numbers. Fu and Shen [
2] introduced a complex-valued grade of fuzzy membership functions to the real part and the imaginary part to define fuzzy complex numbers. There were some studies that dealt with the fuzzy inner product [
4,
5,
6] and the fuzzy Hilbert space [
7,
8]. Recently, we [
9] discussed the absence of non-trivial fuzzy inner product spaces and the Cauchy-Schwartz inequality in the fuzzy real number system.
In this paper, we discuss more properties of the complex fuzzy numbers as an extension of the previous study [
1]. This approach is different from Buckley’s [
1]. We deal with complex fuzzy numbers, not “fuzzy complex numbers”.
In
Section 3 and
Section 4, the complex fuzzy numbers (CFNs) are categorized into two types, as CFNs of type I for the polar form and CFNs of type II for the Cartesian form. The basic properties of the operations in each category are checked.
A fuzzy Hilbert space has been introduced in [
7,
8]. This paper suggests a complex fuzzy inner product space based on our new approach. In
Section 5, we discuss the complex fuzzy inner product on each category of CFN, which shows that, unlike the complex number, the complex fuzzy number of the polar form (type I) has no relation to that of the Cartesian form (type II). In fact, the non-existence of inner products on CFN of type I is proved. We introduce the definition of a complex fuzzy inner product space for type II. Also, several properties of the fuzzy inner product space for type II have been proposed from the modulus defined in
Section 5. Especially, the Cauchy-Schwartz inequality for type II is proved in in a compact way, not only the one for fuzzy real numbers. In fact, it was already dealt with in [
7], however they proved every case in a very complicated way. In this paper, we prove the Cauchy-Schwartz inequality in a much simpler way in a general point of view.
In
Section 6, we introduce a complex fuzzy scalar product and investigate its properties.
2. Preliminaries
In this section, we provide basic definitions and notations for this study.
Definition 1 ([
10] (p. 390)).
A mapping is called a fuzzy real number with α-level set , if it satisfies the following conditions:(i) there exists such that
(ii) for each , there exist real numbers such that the α-level set is equal to the closed interval
Remark 1. The condition (ii) of Definition 1 is equivalent to convex and upper semi continuous:
(1) a fuzzy real number η is convex if where
(2) a fuzzy real number η is called upper semi-continuous if for all and with , there is such that i.e., for all and is open in the usual topology of
The set of all fuzzy real numbers is denoted by
. If
and
whenever
, then
is called a non-negative fuzzy real number and
denotes the set of all non-negative fuzzy real numbers. We note that real number
for all
and all
. Each
can be considered as the fuzzy real number
denoted by
hence it follows that
can be embedded in
.
Definition 2 ([
11] (p. 216)).
The arithmetic operations and ⊘ on are defined bywhich are special cases of Zadeh’s extension principles. Definition 3 ([
11] (p. 216, Equation (2.7))).
The absolute value of is defined by Lemma 1 ([
11] (p. 217)).
Let and . Then for all , Definition 4 ([
11]).
Let and for all . Define a partial ordering by in if and only if for all . The strict inequality in is defined by if and only if for all . 3. Complex Fuzzy Numbers of Type I
Recall that the polar representation
of a complex number, where
and
[
3]. In this section, we consider its extension in fuzzy category, called complex fuzzy numbers of type I, and investigate their basic properties under some structure.
Definition 5 ([
3] (p. 171)).
A complex fuzzy set S of type I defined on a universe of discourse U, is characterized by a membership functionthat assigns a complex-valued grade of membership in S where and are both real-valued and is a fuzzy real number on U. Here, is called the amplitude of . The complex fuzzy set
S may be represented as the set of
ordered pairsSet . We now give examples of a complex fuzzy set S of type I.
Example 1. Let us consider a complex fuzzy setdefined by Then can be expressed in Figure 1. Example 2 ([
3] (p. 184, Equation (49))).
Let U be the set of financial indicators or indexes of the American economy. Possible elements of this set are unemployment rate, inflation, interest rates, growth rate, GDP, Dow-Jones industrial average, etc. Let V be the set of financial indicators of the Japanese Economy. Let the complex fuzzy relation represent the relation of influence of American financial indexes on Japanese financial indexes: y is influenced by x”, where and . The membership function for the relation and , can be presented by complex valued, with an amplitude term and a phase term. The amplitude term indicates the degree of influence of an American financial index on a Japanese financial index. Consider, for example, , i.e., the grade of membership associated with the statement: “American growth rate influences Japanese Export”. Assume the interactions between American and Japanese financial indicators are measured in the limited time frame of 12 months, then it can be represented byNote that the amplitude term was selected to be 0.8, similar to the grade of membership of a traditional fuzzy set. The phase term was chosen to be as an average of three-five months, normalized by 12 months.
Consider the case both and respectively, which given and .
Definition 6. A mapping (or respectively) is called a complex fuzzy number (CFN) on or , respectively, whose α-level set is denoted byif it satisfies two axioms; (i) There exists (or , respectively, such that .
(ii) For each , is a compact connected convex set in .
Note that if then there exists real numbers such that
It is obvious that both and can be embedded in . Furthermore, both and can be embedded in . In this section, and will be written by and for the simplicity, respectively.
Example 3. Letwhere Then for all . Example 4. Let and . Definewhere Then . Given
, recall that the definition of
given by
Let
be the set of all
s on
or
Note that each
can be considered as the
defined by
Then, is the extension of . Moreover, can be embedded in
Since each
can be considered as the complex fuzzy number
defined by
it follows that
can be embedded in
In this paper, we focus on based on .
Definition 7. Let and be complex fuzzy numbers on . Then Note that means for all
Note that for each so that . As the square root of a polar form of a complex number, that of a complex fuzzy number is done as follows:
Definition 8. For a on R, we define the square root of bywhere is the amplitude of and defined by Definition 9. The absolute value of of type
I is defined by The Definition 9 implies
Based on [
3] (p. 181), Definitions 10 and 11 are suggested.
Definition 10. The arithmetic operation ⊕ is given bywhere can be defined by . Remark that, in Definition 10, can be defined in several ways as follows;
(i)
(ii)
(iii)
Similarly, we can think the following definitions in may cases related to angle terms.
Definition 11. (i) The arithmetic operation ⊖ is given bywhere can be defined by . (ii) The arithmetic operation ⊗ is given by where can be defined by .
(iii) The arithmetic operation ⊘ is given by where can be defined by .
Lemma 2. Let , and Then for all ,
(i)
(ii)
(iii)
(iv) if , ,
(v)
4. Complex Fuzzy Numbers of Type II
Note that each
can be considered as the
of type II,
, defined by
where “
” is the
imaginary unit of a complex fuzzy number of type
, (not of a complex number). Then,
is the extension of
. Moreover,
can be embedded in
In this section,
will be written by
for the simplicity.
Definition 12. A complex fuzzy set S of type defined on a universe of discourse U, is characterized by a membership functionthat assigns a complex-valued grade of fuzzy membership in S where both and are fuzzy real numbers on S. Definition 13 ([
2] (p. 1405)).
Let and be complex fuzzy numbers where and d are fuzzy real numbers. The basic arithmetic operations on and are defined as follows;(i) Addition: ,
(ii) Subtraction: ,
(iii) Multiplication:
(iv) Division:
(v) Conjugate:
Remark 2. In [2] (p. 1405), for , the definition on the modulus of complex fuzzy number of type II is given bywhich satisfies . However, given a fuzzy real number need not be greater than or equal to . For example, let be defined by Hence
Thus the definition on the modulus might need to be changed as follows:
Definition 14. The modulus of a complex fuzzy number of type II is Note that the modulus of the Definition 14 is different from the absolute value of the Definition 9 even though they are equivalent in The triangle inequality on modulus may be shown in Theorem 1 with respect to type II.
Theorem 1. Given two fuzzy real numbers it holds that Proof. Let
be given. Recall that for any fuzzy real number
with
it holds that
Then
Similarly, we get □
5. Complex Fuzzy Inner Product Space
In this section, we introduce the definition and investigate some properties of a complex fuzzy inner product space for type
. We will use operations in [
2] (p. 1405).
Definition 15. Let X be a vector space over . Assume the mappings are symmetric and non-decreasing in both arguments, and that and . Let . The quadruple is called a fuzzy normed space [12] with the fuzzy norm , if the following conditions are satisfied: (F1) if , then
(F2) if and only if ,
(F3) for and ,
(F4) for all ,
(F4L) whenever and
(F4R) whenever and
Here, we fix and for all and we write .
Definition 16. Let X be a vector space over A complex-valued fuzzy inner product on X is a mapping such that for all vectors ans , we have
,
,
if
if and only if .
The vector space X with a complex-valued fuzzy inner product is called a complex fuzzy inner product space.
5.1. Non-Existence of the Inner Product on s of Type I
In this subsection, a complex fuzzy inner product in view of type I can not be defined. Let
V be a given complex
n-dimensional vector space. To show by a contradiction, assume that
is a complex fuzzy inner product on
It is well known that there is a basis
on a real vector space
Let
and
Recall that, for
the
is given by
Lemma 3. If then for some function satisfying
Proof. Assume
and let
for some fuzzy real number
and for a function
Then, Equation (
3) says that, for
which implies that
for
For
, it also does that
which gives both
and
Thus we get
□
The following example shows that the inner product of CFN of type I on a vector space cannot be defined.
Example 5. Let and From the Lemma 3, there are two functions such that and satisfying and Then Thus, we getwhich implies from the α-level sets: Therefore, which is a contraction.
5.2. Complex Fuzzy Inner Product Spaces Based on s of Type II
A complex fuzzy inner product on
X defines a fuzzy number
for all
In fact,
from the the positive-definite property of an inner product.
To begin with, for real numbers Especially, with .
Theorem 2. Given a complex fuzzy inner product space and for given two element if for some fuzzy real numbers then and for some real numbers
Proof. Note that
implies that
is a fuzzy real number. Thus
and so
for some
And, from
we get
which implies that
thus
for some
□
We give a simple application regarding the inner product of complex fuzzy numbers which is of type II.
Example 6. Let be a given inner product of some Hilbert space X over . If is given by wherethat is, (Case I) If , then(Case II) If , then Then and are clearly holds. For , Hence is an inner product of the given Hilbert space X.
Remark 3. Theorem 2 shows that an inner product complex fuzzy space is trivial. To find more meaningful complex fuzzy space, we will change the condition of positive definiteness in Definition 16 to that of non-degeneracy (see the Section 5). Lemma 4. ([
7] (Lemma 3.2)).
A real fuzzy inner product space X together with its corresponding norm satisfy the Cauchy-Schwartz inequalityfor all . From now on, the result of Theorem 2 is not used, which enables us to apply the arguments below to the real fuzzy inner product space by letting the imaginary part be
Remark 4. Given a complex fuzzy number where both x and y are fuzzy real numbers, and given the equalitiesandhold. Remark 5. For a vector v in a fuzzy inner product space and for which implies and for each The following lemma is easily checked:
Lemma 5. Given a fuzzy real number
(i) if then and
(ii) if then and
Theorem 3. For vectors , and for each we have Hence, it holds that
Proof. Since all of
and
are fuzzy real numbers, it suffices to show that the inequality
holds for each
If
w is a zero vector
, then
which implies
and so the theorem holds. Assume that
w is not a zero vector. Then from the Definition 16 (IP5),
Denote
by fuzzy real numbers
x and
Let
and put
related to
and
in a similar way. Consider
Then, the inequality
holds and
becomes a fuzzy real number. Thus we can rewrite the equality as follows:
Similarly, we get
which gives
and
□
6. Complex Fuzzy Scalar Product
We already saw that no inner product can exist on the complex fuzzy numbers of type I. In Linear Algebra, recall the concept of a scalar product, which is a weaker version of the concept on an inner product. We introduce a complex fuzzy scalar product for a generalization of a complex fuzzy inner product. In this section, does not restrict to the case of type II, except Theorem 4.
Definition 17. Let X be a vector space over A complex-valued fuzzy scalar product on X is a mapping such that for all vectors ans , we have
,
()
whenever and
()
whenever and
The vector space X with a complex-valued fuzzy scalar product is called a complex fuzzy scalar product space.
Theorem 4. Any complex-valued fuzzy inner product, on a vector space X over is a complex-valued fuzzy scalar product.
Proof. It suffices to show that both
and
hold. To begin with, recall that
Let
Note that if both
s and
t are nonnegative, then Theorem 3 gives
so we get either
or
holds.
To show
consider its hypothesis,
and
which implies either
or
holds, in other words, either
or
Thus we get either
or
and obtain the inequality in
To show
consider its hypothesis,
and
which implies either
or
holds (even in case that either
s or
t is negative). Thus we get either
or
and obtain the inequality in
□
Remark 6. Theorem 4 is meaningful only in case of type II. See Section 5.1. Lemma 6. () is equivalent to Proof. Assume the Equation (
7) holds. Given
s and
t satisfying the hypothesis of (
), let
Then,
from the Equation (
7). The convexity and the hypothesis of (
) say that either
or
which implies that, at least, one of
and
is bigger than or equal to
Therefore,
Conversely, suppose that (
) holds. To show by contradiction, assume that there exist a number
and vectors
v and
w such that
Then we can find two positive numbers
s and
t satisfying
and
Then, both of
and
is less than
which, together with (
), gives
It is a contradiction. □
Lemma 7. () is equivalent to Proof. Assume the Equation (
8) holds. Given
s and
t satisfying the hypothesis of (
), the conclusion of (
) holds trivially if one of
or
is zero. So assume that both of them are greater than zero. Let
and
Then, both
and
hold. Thus, the Equation (
8) and the nondecreasing property of
give
which, together with the convexity property, implies
Conversely, suppose that () holds. Let be given.
Case (1)
For
and
both
and
are greater than or equal to
thus (
) says that
Case (2)
The Equation (
8) holds since
□
A complex fuzzy scalar product on
X defines a fuzzy number
for all
Lemmas 6 and 7 imply that
Theorem 5. For vectors , we have the following inequalities Proof. (ii) By the definition and (i), we have
□