In this paper, we introduce the concept of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy double cosets of a bipolar fuzzy and bipolar anti-fuzzy subgroups. We also establish these concepts to bipolar fuzzy and bipolar anti-fuzzy HX subgroups of a HX group with suitable examples. Also we discuss some of their relative properties.
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results.
A Study on Intuitionistic Multi-Anti Fuzzy Subgroups mathsjournal
For any intuitionistic multi-fuzzy set A = { < x , µA(x) , νA(x) > : x∈X} of an universe set X, we study the set [A](α, β) called the (α, β)–lower cut of A. It is the crisp multi-set { x∈X : µi(x) ≤ αi , νi(x) ≥ βi , ∀i } of X. In this paper, an attempt has been made to study some algebraic structure of intuitionistic multi-anti fuzzy subgroups and their properties with the help of their (α, β)–lower cut sets
This paper presents a common coupled fixed point theorem for two pairs of w-compatible self-mappings (F, G) and (f) in a metric space (X, d). The mappings satisfy a generalized rational contractive condition. The paper proves that if f(X) is a complete subspace of X, then F, G, and f have a unique common coupled fixed point of the form (u, u) in X × X. This result generalizes and improves previous related theorems by removing the completeness assumption on the entire space X. An example is also provided to support the usability of the theorem.
This document presents a new coupled fixed point theorem for mappings having the mixed monotone property in partially ordered metric spaces. Specifically:
1) The theorem establishes the existence of a coupled fixed point for a mapping F that satisfies a contraction-type condition and has the mixed monotone property in a partially ordered, complete metric space.
2) It is shown that the coupled fixed point can be unique under additional conditions involving midpoint lower or upper bound properties.
3) An estimate is provided for the convergence rate as the iterates of the mapping F converge to the coupled fixed point.
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric SpaceIOSR Journals
The purpose of this work is to extend and generalize some common fixed point theorems for Expansive type mappings in complete cone metric spaces. We are attempting to generalize the several well- known recent results. Mathematical subject classification; 54H25, 47H10
The document summarizes existing research on establishing the existence and uniqueness of coupled fixed points for contraction mappings on partially ordered metric spaces. It presents several key theorems:
1) Theorems by Geraghty, Amini-Harandi and Emami, and Gnana Bhaskar and Lakshmikantham establish the existence of unique fixed points for contraction mappings on complete metric spaces and partially ordered metric spaces.
2) Choudhury and Kundu extended these results to Geraghty contractions by introducing an altering distance function.
3) GVR Babu and P. Subhashini further generalized the results to coupled fixed points for Geraghty contractions using an altering distance
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results.
A Study on Intuitionistic Multi-Anti Fuzzy Subgroups mathsjournal
For any intuitionistic multi-fuzzy set A = { < x , µA(x) , νA(x) > : x∈X} of an universe set X, we study the set [A](α, β) called the (α, β)–lower cut of A. It is the crisp multi-set { x∈X : µi(x) ≤ αi , νi(x) ≥ βi , ∀i } of X. In this paper, an attempt has been made to study some algebraic structure of intuitionistic multi-anti fuzzy subgroups and their properties with the help of their (α, β)–lower cut sets
This paper presents a common coupled fixed point theorem for two pairs of w-compatible self-mappings (F, G) and (f) in a metric space (X, d). The mappings satisfy a generalized rational contractive condition. The paper proves that if f(X) is a complete subspace of X, then F, G, and f have a unique common coupled fixed point of the form (u, u) in X × X. This result generalizes and improves previous related theorems by removing the completeness assumption on the entire space X. An example is also provided to support the usability of the theorem.
This document presents a new coupled fixed point theorem for mappings having the mixed monotone property in partially ordered metric spaces. Specifically:
1) The theorem establishes the existence of a coupled fixed point for a mapping F that satisfies a contraction-type condition and has the mixed monotone property in a partially ordered, complete metric space.
2) It is shown that the coupled fixed point can be unique under additional conditions involving midpoint lower or upper bound properties.
3) An estimate is provided for the convergence rate as the iterates of the mapping F converge to the coupled fixed point.
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric SpaceIOSR Journals
The purpose of this work is to extend and generalize some common fixed point theorems for Expansive type mappings in complete cone metric spaces. We are attempting to generalize the several well- known recent results. Mathematical subject classification; 54H25, 47H10
The document summarizes existing research on establishing the existence and uniqueness of coupled fixed points for contraction mappings on partially ordered metric spaces. It presents several key theorems:
1) Theorems by Geraghty, Amini-Harandi and Emami, and Gnana Bhaskar and Lakshmikantham establish the existence of unique fixed points for contraction mappings on complete metric spaces and partially ordered metric spaces.
2) Choudhury and Kundu extended these results to Geraghty contractions by introducing an altering distance function.
3) GVR Babu and P. Subhashini further generalized the results to coupled fixed points for Geraghty contractions using an altering distance
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
In this article we assume that experts express their view points by way of approximation of Triangular
fuzzy numbers. We take the help of fuzzy set theory concept to model the situation and present a method to
aggregate these approximations of triangular fuzzy numbers to obtain an overall approximation of
triangular fuzzy number for each system and then linear ordering done before the best system is chosen. A
comparison has been made betweenapproximation of triangular fuzzy systems and the corresponding fuzzy
triangular numbers systems. The notions like fuzziness and ambiguity for the approximation of triangular
fuzzy numbers are also found.
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
In this article we assume that experts express their view points by way of approximation of Triangular
fuzzy numbers. We take the help of fuzzy set theory concept to model the situation and present a method to
aggregate these approximations of triangular fuzzy numbers to obtain an overall approximation of
triangular fuzzy number for each system and then linear ordering done before the best system is chosen. A
comparison has been made betweenapproximation of triangular fuzzy systems and the corresponding fuzzy
triangular numbers systems. The notions like fuzziness and ambiguity for the approximation of triangular
fuzzy numbers are also found.
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
In this article we assume that experts express their view points by way of approximation of Triangular fuzzy numbers. We take the help of fuzzy set theory concept to model the situation and present a method to aggregate these approximations of triangular fuzzy numbers to obtain an overall approximation of triangular fuzzy number for each system and then linear ordering done before the best system is chosen. A comparison has been made between approximation of triangular fuzzy systems and the corresponding fuzzy triangular numbers systems. The notions like fuzziness and ambiguity for the approximation of triangular fuzzy numbers are also found.
Y.B.Jun et al. [9] introduced the notion of Cubic sets and Cubic subgroups. In this paper we introduced the
notion of cubic BF- Algebra i.e., an interval-valued BF-Algebra and an anti fuzzy BF-Algebra. Intersection of two cubic
BF- Algebras is again a cubic BF-Algebra is also studied.
SOLVING BVPs OF SINGULARLY PERTURBED DISCRETE SYSTEMSTahia ZERIZER
In this article, we study boundary value problems of a large
class of non-linear discrete systems at two-time-scales. Algorithms are given to implement asymptotic solutions for any order of approximation.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Intuitionistic Fuzzification of T-Ideals in Bci-Algebrasiosrjce
This document discusses intuitionistic fuzzification of T-ideals in BCI-algebras. It begins by introducing preliminaries on BCI-algebras, fuzzy sets, intuitionistic fuzzy sets, ideals, and T-ideals. It then defines intuitionistic fuzzy T-ideals and closed intuitionistic fuzzy T-ideals. Several theorems are provided, showing that every intuitionistic fuzzy T-ideal is also an intuitionistic fuzzy ideal, intuitionistic fuzzy p-ideal, and intuitionistic fuzzy H-ideal in BCI-algebras.
An approach to Fuzzy clustering of the iris petals by using Ac-meansijsc
This paper proposes a definition of a fuzzy partition element based on the homomorphism between type-1 fuzzy sets and the three-valued Kleene algebra. A new clustering method
based on the C-means algorithm, using the defined partition, is presented in this paper, which will
be validated with the traditional iris clustering problem by measuring its petals.
This document provides definitions and notation for set theory concepts. It defines what a set is, ways to describe sets (explicitly by listing elements or implicitly using set builder notation), and basic set relationships like subset, proper subset, union, intersection, complement, power set, and Cartesian product. It also discusses Russell's paradox and defines important sets like the natural numbers. Key identities for set operations like idempotent, commutative, associative, distributive, De Morgan's laws, and complement laws are presented. Proofs of identities using logical equivalences and membership tables are demonstrated.
The paper reports on an iteration algorithm to compute asymptotic solutions at any order for a wide class of nonlinear
singularly perturbed difference equations.
The document discusses partial differential equations (PDEs) and numerical methods for solving them. It begins by defining PDEs as equations involving derivatives of an unknown function with respect to two or more independent variables. PDEs describe many physical phenomena involving variations across space and time, such as fluid flow, heat transfer, electromagnetism, and weather prediction. The document then focuses on solving elliptic, parabolic, and hyperbolic PDEs numerically using finite difference and finite element methods. It provides examples of discretizing and solving the Laplace, heat, and wave equations to estimate unknown functions.
Simultaneous Triple Series Equations Involving Konhauser Biorthogonal Polynom...IOSR Journals
Biorthogonal polynomials are of great interest for Physicists.Spencer and Fano [9] used the biorthogonal polynomials (for the case k = 2) in carrying out calculations involving penetration of gamma rays through matter.In the present paper an exact solution of simultaneous triple series equations involving Konhauser-biorthogonal polynomials of first kind of different indices is obtained by multiplying factor technique due to Noble.[4] This technique has been modified by Thakare [10, 11] to solve dual series equations involving orthogonal polynomials which led to disprove a possible conjecture of Askey [1] that a dual series equation involving Jacobi polynomials of different indices can not be solved. In this paper the solution of simultaneous triple series equations involving generalized Laguerre polynomials also have been discussed as a charmfull particular case.
Intuitionistic Fuzzy W- Closed Sets and Intuitionistic Fuzzy W -ContinuityWaqas Tariq
The aim of this paper is to introduce and study the concepts of intuitionistic fuzzy w- closed sets, intuitionistic fuzzy w-continuity and inttuitionistic fuzzy w-open & intuitionistic fuzzy w-closed mappings in intuitionistic fuzzy topological spaces.
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroupsmathsjournal
In this paper, we introduce the concept of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy double cosets of a bipolar fuzzy and bipolar anti-fuzzy subgroups. We also establish these concepts to bipolar fuzzy and bipolar anti-fuzzy HX subgroups of a HX group with suitable examples. Also we discuss some of their relative properties.
A Study on Intuitionistic Multi-Anti Fuzzy Subgroupsmathsjournal
This document summarizes research on intuitionistic multi-anti fuzzy subgroups. Key points:
- Intuitionistic multi-fuzzy sets allow elements to have multiple membership values. Intuitionistic multi-anti fuzzy subgroups are intuitionistic multi-fuzzy sets that satisfy certain algebraic properties under group operations.
- The (α,β)-lower cut of an intuitionistic multi-fuzzy set is the crisp multi-set of elements whose membership and non-membership values are below α and above β thresholds. Properties of (α,β)-lower cuts are used to study intuitionistic multi-anti fuzzy subgroups.
- Definitions are provided for intuitionistic multi-fuzzy sets, intuitionistic multi-anti fuzzy subgroups
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results
This document discusses the probability that an element of a metacyclic 2-group fixes a set. It begins by providing background information on metacyclic groups and related concepts such as commutativity degree. It then summarizes previous works that have studied the probability of a group element fixing a set. The main results presented calculate the probability for various metacyclic 2-groups of negative type with nilpotency class of at least two. In particular, it determines the probability for metacyclic 2-groups of negative type with nilpotency class of at least three. It also calculates the probability for other specific metacyclic 2-group structures.
On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...IOSR Journals
This document introduces and studies various types of fuzzy open sets in fuzzy topological spaces, including fuzzy δ-open sets, fuzzy ∆-open sets, fuzzy γ-open sets, fuzzy θ-open sets, and fuzzy regular open sets. It defines each type of fuzzy open set and establishes relationships between them. The document also introduces several types of fuzzy separation axioms in fuzzy topological spaces, including fuzzy δT0 spaces, and proves some properties and theorems about these concepts. Figures and examples are provided to illustrate the concepts and show that the converse of some relationships between fuzzy open set types do not always hold.
Interval valued intuitionistic fuzzy homomorphism of bf algebrasAlexander Decker
This document discusses interval-valued intuitionistic fuzzy homomorphisms of BF-algebras. It begins with introducing BF-algebras and defining interval-valued intuitionistic fuzzy sets. It then defines interval-valued intuitionistic fuzzy ideals of BF-algebras and provides an example. Interval-valued intuitionistic fuzzy homomorphisms of BF-algebras are introduced and some properties are investigated, including showing that the image of an interval-valued intuitionistic fuzzy ideal under a homomorphism is also an interval-valued intuitionistic fuzzy ideal if it satisfies the "sup-inf" property.
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...mathsjournal
In this paper, we give some new definition of Compatible mappings of type (P), type (P-1) and type (P-2) in intuitionistic generalized fuzzy metric spaces and prove Common fixed point theorems for six mappings
under the conditions of compatible mappings of type (P-1) and type (P-2) in complete intuitionistic fuzzy
metric spaces. Our results intuitionistically fuzzify the result of Muthuraj and Pandiselvi [15]
Mathematics subject classifications: 45H10, 54H25
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
In this article we assume that experts express their view points by way of approximation of Triangular
fuzzy numbers. We take the help of fuzzy set theory concept to model the situation and present a method to
aggregate these approximations of triangular fuzzy numbers to obtain an overall approximation of
triangular fuzzy number for each system and then linear ordering done before the best system is chosen. A
comparison has been made betweenapproximation of triangular fuzzy systems and the corresponding fuzzy
triangular numbers systems. The notions like fuzziness and ambiguity for the approximation of triangular
fuzzy numbers are also found.
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
In this article we assume that experts express their view points by way of approximation of Triangular
fuzzy numbers. We take the help of fuzzy set theory concept to model the situation and present a method to
aggregate these approximations of triangular fuzzy numbers to obtain an overall approximation of
triangular fuzzy number for each system and then linear ordering done before the best system is chosen. A
comparison has been made betweenapproximation of triangular fuzzy systems and the corresponding fuzzy
triangular numbers systems. The notions like fuzziness and ambiguity for the approximation of triangular
fuzzy numbers are also found.
AGGREGATION OF OPINIONS FOR SYSTEM SELECTION USING APPROXIMATIONS OF FUZZY NU...mathsjournal
In this article we assume that experts express their view points by way of approximation of Triangular fuzzy numbers. We take the help of fuzzy set theory concept to model the situation and present a method to aggregate these approximations of triangular fuzzy numbers to obtain an overall approximation of triangular fuzzy number for each system and then linear ordering done before the best system is chosen. A comparison has been made between approximation of triangular fuzzy systems and the corresponding fuzzy triangular numbers systems. The notions like fuzziness and ambiguity for the approximation of triangular fuzzy numbers are also found.
Y.B.Jun et al. [9] introduced the notion of Cubic sets and Cubic subgroups. In this paper we introduced the
notion of cubic BF- Algebra i.e., an interval-valued BF-Algebra and an anti fuzzy BF-Algebra. Intersection of two cubic
BF- Algebras is again a cubic BF-Algebra is also studied.
SOLVING BVPs OF SINGULARLY PERTURBED DISCRETE SYSTEMSTahia ZERIZER
In this article, we study boundary value problems of a large
class of non-linear discrete systems at two-time-scales. Algorithms are given to implement asymptotic solutions for any order of approximation.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Intuitionistic Fuzzification of T-Ideals in Bci-Algebrasiosrjce
This document discusses intuitionistic fuzzification of T-ideals in BCI-algebras. It begins by introducing preliminaries on BCI-algebras, fuzzy sets, intuitionistic fuzzy sets, ideals, and T-ideals. It then defines intuitionistic fuzzy T-ideals and closed intuitionistic fuzzy T-ideals. Several theorems are provided, showing that every intuitionistic fuzzy T-ideal is also an intuitionistic fuzzy ideal, intuitionistic fuzzy p-ideal, and intuitionistic fuzzy H-ideal in BCI-algebras.
An approach to Fuzzy clustering of the iris petals by using Ac-meansijsc
This paper proposes a definition of a fuzzy partition element based on the homomorphism between type-1 fuzzy sets and the three-valued Kleene algebra. A new clustering method
based on the C-means algorithm, using the defined partition, is presented in this paper, which will
be validated with the traditional iris clustering problem by measuring its petals.
This document provides definitions and notation for set theory concepts. It defines what a set is, ways to describe sets (explicitly by listing elements or implicitly using set builder notation), and basic set relationships like subset, proper subset, union, intersection, complement, power set, and Cartesian product. It also discusses Russell's paradox and defines important sets like the natural numbers. Key identities for set operations like idempotent, commutative, associative, distributive, De Morgan's laws, and complement laws are presented. Proofs of identities using logical equivalences and membership tables are demonstrated.
The paper reports on an iteration algorithm to compute asymptotic solutions at any order for a wide class of nonlinear
singularly perturbed difference equations.
The document discusses partial differential equations (PDEs) and numerical methods for solving them. It begins by defining PDEs as equations involving derivatives of an unknown function with respect to two or more independent variables. PDEs describe many physical phenomena involving variations across space and time, such as fluid flow, heat transfer, electromagnetism, and weather prediction. The document then focuses on solving elliptic, parabolic, and hyperbolic PDEs numerically using finite difference and finite element methods. It provides examples of discretizing and solving the Laplace, heat, and wave equations to estimate unknown functions.
Simultaneous Triple Series Equations Involving Konhauser Biorthogonal Polynom...IOSR Journals
Biorthogonal polynomials are of great interest for Physicists.Spencer and Fano [9] used the biorthogonal polynomials (for the case k = 2) in carrying out calculations involving penetration of gamma rays through matter.In the present paper an exact solution of simultaneous triple series equations involving Konhauser-biorthogonal polynomials of first kind of different indices is obtained by multiplying factor technique due to Noble.[4] This technique has been modified by Thakare [10, 11] to solve dual series equations involving orthogonal polynomials which led to disprove a possible conjecture of Askey [1] that a dual series equation involving Jacobi polynomials of different indices can not be solved. In this paper the solution of simultaneous triple series equations involving generalized Laguerre polynomials also have been discussed as a charmfull particular case.
Intuitionistic Fuzzy W- Closed Sets and Intuitionistic Fuzzy W -ContinuityWaqas Tariq
The aim of this paper is to introduce and study the concepts of intuitionistic fuzzy w- closed sets, intuitionistic fuzzy w-continuity and inttuitionistic fuzzy w-open & intuitionistic fuzzy w-closed mappings in intuitionistic fuzzy topological spaces.
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroupsmathsjournal
In this paper, we introduce the concept of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy double cosets of a bipolar fuzzy and bipolar anti-fuzzy subgroups. We also establish these concepts to bipolar fuzzy and bipolar anti-fuzzy HX subgroups of a HX group with suitable examples. Also we discuss some of their relative properties.
A Study on Intuitionistic Multi-Anti Fuzzy Subgroupsmathsjournal
This document summarizes research on intuitionistic multi-anti fuzzy subgroups. Key points:
- Intuitionistic multi-fuzzy sets allow elements to have multiple membership values. Intuitionistic multi-anti fuzzy subgroups are intuitionistic multi-fuzzy sets that satisfy certain algebraic properties under group operations.
- The (α,β)-lower cut of an intuitionistic multi-fuzzy set is the crisp multi-set of elements whose membership and non-membership values are below α and above β thresholds. Properties of (α,β)-lower cuts are used to study intuitionistic multi-anti fuzzy subgroups.
- Definitions are provided for intuitionistic multi-fuzzy sets, intuitionistic multi-anti fuzzy subgroups
In this paper we introduce the notions of Fuzzy Ideals in BH-algebras and the notion
of fuzzy dot Ideals of BH-algebras and investigate some of their results
This document discusses the probability that an element of a metacyclic 2-group fixes a set. It begins by providing background information on metacyclic groups and related concepts such as commutativity degree. It then summarizes previous works that have studied the probability of a group element fixing a set. The main results presented calculate the probability for various metacyclic 2-groups of negative type with nilpotency class of at least two. In particular, it determines the probability for metacyclic 2-groups of negative type with nilpotency class of at least three. It also calculates the probability for other specific metacyclic 2-group structures.
On Some Types of Fuzzy Separation Axioms in Fuzzy Topological Space on Fuzzy ...IOSR Journals
This document introduces and studies various types of fuzzy open sets in fuzzy topological spaces, including fuzzy δ-open sets, fuzzy ∆-open sets, fuzzy γ-open sets, fuzzy θ-open sets, and fuzzy regular open sets. It defines each type of fuzzy open set and establishes relationships between them. The document also introduces several types of fuzzy separation axioms in fuzzy topological spaces, including fuzzy δT0 spaces, and proves some properties and theorems about these concepts. Figures and examples are provided to illustrate the concepts and show that the converse of some relationships between fuzzy open set types do not always hold.
Interval valued intuitionistic fuzzy homomorphism of bf algebrasAlexander Decker
This document discusses interval-valued intuitionistic fuzzy homomorphisms of BF-algebras. It begins with introducing BF-algebras and defining interval-valued intuitionistic fuzzy sets. It then defines interval-valued intuitionistic fuzzy ideals of BF-algebras and provides an example. Interval-valued intuitionistic fuzzy homomorphisms of BF-algebras are introduced and some properties are investigated, including showing that the image of an interval-valued intuitionistic fuzzy ideal under a homomorphism is also an interval-valued intuitionistic fuzzy ideal if it satisfies the "sup-inf" property.
Common Fixed Point Theorems in Compatible Mappings of Type (P*) of Generalize...mathsjournal
In this paper, we give some new definition of Compatible mappings of type (P), type (P-1) and type (P-2) in intuitionistic generalized fuzzy metric spaces and prove Common fixed point theorems for six mappings
under the conditions of compatible mappings of type (P-1) and type (P-2) in complete intuitionistic fuzzy
metric spaces. Our results intuitionistically fuzzify the result of Muthuraj and Pandiselvi [15]
Mathematics subject classifications: 45H10, 54H25
This document presents definitions and results regarding L-fuzzy normal sub l-groups. It begins with introductions and preliminaries on L-fuzzy sets, L-fuzzy subgroups, and L-fuzzy sub l-groups. It then presents 8 theorems on properties of L-fuzzy normal sub l-groups, such as conditions for an L-fuzzy subset to be an L-fuzzy normal sub l-group, the intersection of L-fuzzy normal sub l-groups also being an L-fuzzy normal sub l-group, and conditions where an L-fuzzy sub l-group is necessarily an L-fuzzy normal sub l-group. The document references 6 sources and is focused on developing the theory of L-fuzzy
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...mathsjournal
In this paper, we give some new definition of Compatible mappings of type (P), type (P-1) and type (P-2) in intuitionistic generalized fuzzy metric spaces and prove Common fixed point theorems for six mappings under the conditions of compatible mappings of type (P-1) and type (P-2) in complete intuitionistic fuzzy metric spaces. Our results intuitionistically fuzzify the result of Muthuraj and Pandiselvi [15]
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...mathsjournal
In this paper, we give some new definition of Compatible mappings of type (P), type (P-1) and type (P-2) in intuitionistic generalized fuzzy metric spaces and prove Common fixed point theorems for six mappings under the conditions of compatible mappings of type (P-1) and type (P-2) in complete intuitionistic fuzzy metric spaces.
COMMON FIXED POINT THEOREMS IN COMPATIBLE MAPPINGS OF TYPE (P*) OF GENERALIZE...mathsjournal
In this paper, we give some new definition of Compatible mappings of type (P), type (P-1) and type (P-2) in intuitionistic generalized fuzzy metric spaces and prove Common fixed point theorems for six mappings under the
conditions of compatible mappings of type (P-1) and type (P-2) in complete intuitionistic fuzzy metric spaces. Our results intuitionistically fuzzify the result of Muthuraj and Pandiselvi [15]
Mathematics subject classifications: 45H10, 54H25
This document discusses L-fuzzy sub λ-groups. Key points:
- It defines L-fuzzy sub λ-groups and anti L-fuzzy sub λ-groups, which combine fuzzy set theory with lattice ordered group theory.
- Properties of L-fuzzy sub λ-groups are investigated, such as conditions under which a subset is a sub λ-group. The intersection of two L-fuzzy sub λ-groups is also an L-fuzzy sub λ-group.
- A relationship is established between an L-fuzzy sub λ-group and its complement, which must be an anti L-fuzzy sub λ-group.
- Level subsets of
The document provides an overview of sets and logic. It defines basic set concepts like elements, subsets, unions and intersections. It explains Venn diagrams can be used to represent relationships between sets. Logic is introduced as the study of correct reasoning. Propositions are defined as statements that can be determined as true or false. Logical connectives like conjunction, disjunction and negation are explained through truth tables. Compound statements can be formed using these connectives.
Similar to Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroups (20)
OPTIMIZING SIMILARITY THRESHOLD FOR ABSTRACT SIMILARITY METRIC IN SPEECH DIAR...mathsjournal
Speaker diarization is a critical task in speech processing that aims to identify "who spoke when?" in an
audio or video recording that contains unknown amounts of speech from unknown speakers and unknown
number of speakers. Diarization has numerous applications in speech recognition, speaker identification,
and automatic captioning. Supervised and unsupervised algorithms are used to address speaker diarization
problems, but providing exhaustive labeling for the training dataset can become costly in supervised
learning, while accuracy can be compromised when using unsupervised approaches. This paper presents a
novel approach to speaker diarization, which defines loosely labeled data and employs x-vector embedding
and a formalized approach for threshold searching with a given abstract similarity metric to cluster
temporal segments into unique user segments. The proposed algorithm uses concepts of graph theory,
matrix algebra, and genetic algorithm to formulate and solve the optimization problem. Additionally, the
algorithm is applied to English, Spanish, and Chinese audios, and the performance is evaluated using wellknown similarity metrics. The results demonstrate that the robustness of the proposed approach. The
findings of this research have significant implications for speech processing, speaker identification
including those with tonal differences. The proposed method offers a practical and efficient solution for
speaker diarization in real-world scenarios where there are labeling time and cost constraints.
A POSSIBLE RESOLUTION TO HILBERT’S FIRST PROBLEM BY APPLYING CANTOR’S DIAGONA...mathsjournal
We present herein a new approach to the Continuum hypothesis CH. We will employ a string conditioning,
a technique that limits the range of a string over some of its sub-domains for forming subsets K of R. We
will prove that these are well defined and in fact proper subsets of R by making use of Cantor’s Diagonal
argument in its original form to establish the cardinality of K between that of (N,R) respectively
A Positive Integer 𝑵 Such That 𝒑𝒏 + 𝒑𝒏+𝟑 ~ 𝒑𝒏+𝟏 + 𝒑𝒏+𝟐 For All 𝒏 ≥ 𝑵mathsjournal
According to Bertrand's postulate, we have 𝑝𝑛 + 𝑝𝑛 ≥ 𝑝𝑛+1. Is it true that for all 𝑛 > 1 then 𝑝𝑛−1 + 𝑝𝑛 ≥𝑝𝑛+1? Then 𝑝𝑛 + 𝑝𝑛+3 > 𝑝𝑛+1 + 𝑝𝑛+2where 𝑛 ≥ 𝑁, 𝑁 is a large enough value?
A POSSIBLE RESOLUTION TO HILBERT’S FIRST PROBLEM BY APPLYING CANTOR’S DIAGONA...mathsjournal
We present herein a new approach to the Continuum hypothesis CH. We will employ a string conditioning,
a technique that limits the range of a string over some of its sub-domains for forming subsets K of R. We
will prove that these are well defined and in fact proper subsets of R by making use of Cantor’s Diagonal
argument in its original form to establish the cardinality of K between that of (N,R) respectively.
Moving Target Detection Using CA, SO and GO-CFAR detectors in Nonhomogeneous ...mathsjournal
systems in complex situations. A fundamental problem in radar systems is to automatically detect targets while maintaining a
desired constant false alarm probability. This work studies two detection approaches, the first with a fixed threshold and the
other with an adaptive one. In the latter, we have learned the three types of detectors CA, SO, and GO-CFAR. This research
aims to apply intelligent techniques to improve detection performance in a nonhomogeneous environment using standard
CFAR detectors. The objective is to maintain the false alarm probability and enhance target detection by combining
intelligent techniques. With these objectives in mind, implementing standard CFAR detectors is applied to nonhomogeneous
environment data. The primary focus is understanding the reason for the false detection when applying standard CFAR
detectors in a nonhomogeneous environment and how to avoid it using intelligent approaches.
OPTIMIZING SIMILARITY THRESHOLD FOR ABSTRACT SIMILARITY METRIC IN SPEECH DIAR...mathsjournal
Speaker diarization is a critical task in speech processing that aims to identify "who spoke when?" in an
audio or video recording that contains unknown amounts of speech from unknown speakers and unknown
number of speakers. Diarization has numerous applications in speech recognition, speaker identification,
and automatic captioning. Supervised and unsupervised algorithms are used to address speaker diarization
problems, but providing exhaustive labeling for the training dataset can become costly in supervised
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Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and Bipolar Anti-Fuzzy HX Subgroups
1. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
1
Pseudo Bipolar Fuzzy Cosets of Bipolar Fuzzy and
Bipolar Anti-Fuzzy HX Subgroups
R.Muthuraj1
and M.Sridharan2
1
PG & Research Department of Mathematics, H.H.The Rajah’s College,
Pudukkottai – 622 001, Tamilnadu, India.
2
Department of Mathematics, PSNA College of Engineering and Technology,
Dindigul-624 622, Tamilnadu , India.
ABSTRACT
In this paper, we introduce the concept of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy double cosets
of a bipolar fuzzy and bipolar anti-fuzzy subgroups. We also establish these concepts to bipolar fuzzy and
bipolar anti-fuzzy HX subgroups of a HX group with suitable examples. Also we discuss some of their
relative properties.
KEYWORDS
bipolar fuzzy set, bipolar fuzzy subgroup, bipolar anti-fuzzy subgroup, pseudo bipolar fuzzy cosets, pseudo
bipolar fuzzy double cosets , bipolar fuzzy HX subgroup , bipolar anti-fuzzy HX subgroup.
1. INTRODUCTION
The notion of fuzzy sets was introduced by L.A. Zadeh [15]. Fuzzy set theory has been developed
in many directions by many researchers and has evoked great interest among mathematicians
working in different fields of mathematics. In 1971, Rosenfeld [12] introduced the concept of
fuzzy subgroup. R. Biswas [1] introduced the concept of anti fuzzy subgroup of group. Li
Hongxing [2] introduced the concept of HX group and the authors Chengzhong et al.[4]
introduced the concept of fuzzy HX group. Palaniappan.N. et al.[12] discussed the concepts of
anti-fuzzy group and its Lower level subgroups. Muthuraj.R.,et al.[7],[9] discussed the concepts
of bipolar fuzzy subgroups and bipolar anti fuzzy subgroups and also discussed bipolar fuzzy HX
subgroup and its level sub HX groups, bipolar anti-fuzzy HX subgroups and its lower level sub
HX groups. Bhattacharya [10] introduced fuzzy right coset and fuzzy left coset of a group. B.
Vasantha kandasamy [14] introduced the concept of pseudo fuzzy cosets, and pseudo fuzzy
double cosets of a fuzzy group of a group. In this paper we define the concept of pseudo bipolar
fuzzy cosets, pseudo bipolar fuzzy double cosets of bipolar fuzzy and bipolar anti-fuzzy
subgroups of a group. Also introduce the concept of pseudo bipolar fuzzy cosets and pseudo
bipolar fuzzy double cosets of bipolar fuzzy and bipolar anti-fuzzy HX subgroups of a HX group
and study some of their related properties.
2. PRELIMINARIES
In this section, we site the fundamental definitions that will be used in the sequel. Throughout this
paper, G = (G, *) is a group, e is the identity element of G, and xy, we mean x * y.
2. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
2
2.1 Definition [15]
Let X be any non empty set. A fuzzy subset µ of X is a function µ: X → [0, 1].
2.2 Definition [1]
A fuzzy set µ on G is called fuzzy subgroup of G if for x, y ∈G,
i.µ(xy) ≥ min {µ(x), µ( y)}
ii.µ(x-1
) = µ(x).
2.3 Definition [1]
A fuzzy set µ on G is called an anti- fuzzy subgroup of G if for x, y ∈G,
i.µ(xy)≤ max {µ (x), µ(y)}
ii.µ(x-1
) = µ(x).
2.4 Definition [9]
Let G be a non-empty set. A bipolar-valued fuzzy set or bipolar fuzzy set µ in G is an object
having the form µ={〈x, µ+
(x), µ−
(x)〉 : x∈G} where µ+
: G → [0,1] and µ−
: G → [−1,0] are
mappings. The positive membership degree µ+
(x) denotes the satisfaction degree of an element x
to the property corresponding to a bipolar-valued fuzzy set µ ={〈x, µ+
(x), µ−
(x)〉: x∈G} and the
negative membership degree µ−
(x) denotes the satisfaction degree of an element x to some
implicit counter property corresponding to a bipolar-valued fuzzy set µ = {〈x, µ+
(x), µ−
(x) 〉 :
x∈G}. If µ+
(x) ≠ 0 and µ−
(x) = 0, it is the situation that x is regarded as having only positive
satisfaction for µ = {〈x, µ+
(x), µ−
(x)〉 : x∈G}. If µ+
(x) = 0 and µ−
(x) ≠ 0, it is the situation that x
does not satisfy the property of µ ={〈x, µ+
(x), µ−
(x)〉: x∈G}, but somewhat satisfies the counter
property of µ = {〈x, µ+
(x), µ−
(x)〉 : x∈G}. It is possible for an element x to be such that µ+
(x) ≠ 0
and µ−
(x) ≠ 0 when the membership function of property overlaps that its counter property over
some portion of G. For the sake of simplicity, we shall use the symbol µ = (µ+
,µ−
) for the bipolar-
valued fuzzy set µ = {〈x, µ+
(x), µ−
(x)〉: x∈G}.
2.5 Definition [9]
A bipolar-valued fuzzy set or bipolar fuzzy set µ = ( µ+
, µ−
) is called a bipolar fuzzy
subgroup of G if for x, y ∈G,
i. µ+
(xy) ≥ min {µ+
(x), µ+
(y)}
ii. µ−
(xy) ≤ max {µ−
(x), µ−
(y)}
iii. µ+
(x−1
) = µ+
(x) , µ−
(x−1
) = µ−
(x).
2.6 Definition [9]
A bipolar-valued fuzzy set or bipolar fuzzy set µ = ( µ+
, µ−
) is called a bipolar anti-fuzzy
subgroup of G if for x, y ∈ G,
i.µ+
(xy) ≤ max {µ+
(x), µ+
(y)}
ii.µ−
(xy) ≥ min {µ−
(x), µ−
(y)}
iii.µ+
(x−1
) = µ+
(x) , µ−
(x−1
) = µ−
(x).
3. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
3
3. Pseudo Bipolar Fuzzy Cosets And Pseudo Bipolar Fuzzy Double
Cosets Of Bipolar Fuzzy And Bipolar Anti-Fuzzy Subgroups And
Their Properties:
In this section, we define the concepts of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy
double cosets of a bipolar fuzzy and bipolar anti-fuzzy subgroups of a group and discuss some of
their properties.
3.1 Definition
Let µ = (µ+
,µ−
) be a bipolar fuzzy subgroup of a group G and let a ∈ G. Then the pseudo bipolar
fuzzy coset (aµ)P
= (((aµ)P
)+
, ((aµ)P
) −
) is defined by
i.((aµ)P
)+
(x) = |p(a)| µ+
(x)
ii.((aµ)P
) −
(x) = |p(a)| µ−
(x) ,for every x ∈ G
and for some p∈P, where P = {p(x) / p(x)∈[−1,1] and p (x) ≠ 0 for all x ∈ G }.
3.2 Example
Let G be a Klein’s four group. Then G = {e,a,b,ab} where a2
= e = b2
, ab = ba and e is the identity
element of G. Define a bipolar fuzzy subset +
µ = (µ ,µ )-
on G as,
+
0.6 ,if x = e
µ (x) = 0.4 ,if x = a
0.3 ,if x = b,ab
0.7 , if x = e
µ (x) = 0.6 ,if x = a
0.4 ,if x = b,ab
-
-
-
-
Let us take p as follows
0.8 ,if x = e
0.6 ,if x = a
p(x) =
0.4 ,if x = b
0.3 ,if x = ab
Now we calculate the pseudo bipolar fuzzy coset of +
µ = (µ ,µ )-
.For the identity element e of
the group G, we have p
(eµ) = µ .
For the element a of G, we have
p + +
0.36 ,if x = e
((aµ) ) (x) = p(a) µ (x)= 0.24 ,if x = a
0.18 ,if x = b,ab
4. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
4
p
0.42 ,if x = e
((aµ) ) (x) = p(a) µ (x) = 0.36 ,if x = a
0.24 ,if x = b,ab
- -
-
-
-
For the element b of G, we have
p + +
0.24 ,if x = e
((bµ) ) (x) = p(b) µ (x) = 0.16 ,if x = a
0.12 ,if x = b,ab
p
0.28 ,if x = e
((bµ) ) (x) = p(b) µ (x) = 0.24 ,if x = a
0.16 ,if x = b,ab
- -
-
-
-
For the element ab of G, we have
p + +
0.18 ,if x = e
((abµ) ) (x) = p(ab) µ (x) = 0.12 ,if x = a
0.09 ,if x = b,ab
p
0.21 ,if x = e
((abµ) ) (x) = p(ab) µ (x) = 0.18 ,if x = a
0.12 ,if x = b,ab
- -
-
-
-
Note: The pseudo bipolar fuzzy cosets of +
µ = (µ ,µ )-
are bipolar fuzzy subgroups of G
since + +
µ (e) µ (x)≥ andµ (e) µ (x)≤- -
.
3.3 Definition
Let
+
µ = (µ ,µ )-
be a bipolar anti-fuzzy subgroup of a group G and let a ∈ G. Then the pseudo
bipolar fuzzy coset (aµ)P
= (((aµ)P
)+
, ((aµ)P
) −
) is defined by
i.((aµ)P
)+
(x) = |p(a)| µ+
(x)
ii.((aµ)P
) −
(x) = |p(a)| µ−
(x) , for every x ∈ G and for some
p ∈ P, Where P ={p(x) / p(x) ∈ [−1,1] and p(x) ≠ 0 for all x ∈ G}.
3.4 Example
Let G be a Klein’s four group. Then G = {e,a,b,ab} where a2
= e = b2
, ab = ba and e is the
identity element of G. Define a bipolar fuzzy subset
+
µ = (µ ,µ )-
on G as,
5. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
5
+
0.3 ,if x = e
µ (x) = 0.5 ,if x = a
0.7 ,if x = b,ab
0.4 , if x = e
µ (x) = 0.6 ,if x = a
0.8 ,if x = b,ab
-
-
-
-
Clearly +
µ = (µ ,µ )-
is a bipolar anti-fuzzy subgroup of G.
Let us take p as follows
0.6 ,if x = e
0.5 ,if x = a
p(x) =
0.7 ,if x = b
0.8 ,if x = ab
-
-
-
-
Now we calculate the pseudo bipolar fuzzy coset of +
µ = (µ ,µ )-
.For the identity element e of
the group G ,we have p
(eµ) = µ .
For the element a of G, we have
p + +
0.15 ,if x = e
((aµ) ) (x) = p(a) µ (x) = 0.25 ,if x = a
0.35 ,if x = b,ab
p
0.20 ,if x = e
((aµ) ) (x) = p(a) µ (x) = 0.30 ,if x = a
0.40 ,if x = b,ab
- -
-
-
-
For the element b of G, we have
p + +
0.21 ,if x = e
((bµ) ) (x) = p(b) µ (x) = 0.35 ,if x = a
0.49 ,if x = b,ab
p
0.28 ,if x = e
((bµ) ) (x) = p(b) µ (x) = 0.42 ,if x = a
0.56 ,if x = b,ab
- -
-
-
-
For the element ab of G, we have
6. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
6
p + +
0.24 ,if x = e
((abµ) ) (x) = p(ab) µ (x) = 0.4 ,if x = a
0.56 ,if x = b,ab
p
0.32 ,if x = e
((abµ) ) (x) = p(ab) µ (x) = 0.48 ,if x = a
0.64 ,if x = b,ab
- -
-
-
-
Note: The pseudo bipolar fuzzy cosets of +
µ = (µ ,µ )-
are bipolar anti-fuzzy subgroups
of G since + +
µ (e) µ (x)≤ andµ (e) µ (x)≥- -
.
3.5 Definition
Let µ and φ be any two bipolar fuzzy subgroups of a group G, then pseudo bipolar fuzzy double
coset (µaφ)p
is defined by
i. ((µaφ)p
)+
= ((aµ)p
∩ (aφ)p
)+
ii. ((µaφ)p
)−
= ((aµ)p
∩ (aφ)p
)−
where a∈G for some p∈P.
3.6 Example
Let G ={1, 1,i, i}- - be a group under the binary operation multiplication. Let bipolar fuzzy
subsets +
µ = (µ ,µ )-
and +
φ = (φ ,φ )-
on G are defined as,
+
0.7 ,if x =1
µ (x) = 0.6 ,if x = 1
0.4 ,if x = i, i
-
-
0.6 , if x =1
µ (x) = 0.4 ,if x = 1
0.3 ,if x = i, i
-
-
- -
- -
+
0.8 ,if x =1
φ (x) = 0.5 ,if x = 1
0.3 ,if x = i, i
-
-
0.7 , if x =1
φ (x) = 0.3 ,if x = 1
0.2 ,if x = i, i
-
-
- -
- -
Clearly
+
µ = (µ ,µ )-
and
+
φ = (φ ,φ )-
are bipolar fuzzy subgroups of G.
Let us take p as follows p(x) = − 0.3 for every x∈G, then the pseudo bipolar fuzzy cosets are,
p + +
0.21 ,if x =1
((aµ) ) (x) = p(a) µ (x)= 0.18 ,if x = 1
0.12 ,if x = i, i
-
-
7. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
7
p
0.18 ,if x =1
((aµ) ) (x) = p(a) µ (x) = 0.12 ,if x = 1
0.09 ,if x = i, i
- -
-
- -
- -
p + +
0.24 ,if x =1
((aφ) ) (x) = p(a) φ (x)= 0.15 ,if x = 1
0.09 ,if x = i, i
-
-
p
0.21 ,if x =1
((aφ) ) (x) = p(a) φ (x) = 0.09 ,if x = 1
0.06 ,if x = i, i
- -
-
- -
- -
Now the pseudo bipolar fuzzy double cosets are
p +
0.21 ,if x =1
((µaφ) ) (x) = 0.15 ,if x = 1
0.09 ,if x = i, i
-
-
p
0.18 ,if x =1
((µaφ) ) (x) = 0.09 ,if x = 1
0.06 ,if x = i, i
-
-
- -
- -
3.7 Definition
Let µ and φ be any two bipolar anti-fuzzy subgroups of a group G, then pseudo bipolar fuzzy
double coset (µaφ)p
is defined by
i. ((µaφ)p
)+
= ((aµ)p
∩ (aφ)p
)+
ii. ((µaφ)p
)−
= ((aµ)p
∩ (aφ)p
)−
where a∈G for some p∈P.
3.8 Example
Let G ={1, 1,i, i}- - be a group under the binary operation multiplication. Define bipolar fuzzy
subsets +
µ = (µ ,µ )-
and +
φ = (φ ,φ )-
on G as,
+
0.4 ,if x =1
µ (x) = 0.6 ,if x = 1
0.7 ,if x = i, i
-
-
0.3 , if x =1
µ (x) = 0.4 ,if x = 1
0.6 ,if x = i, i
-
-
- -
- -
+
0.3 ,if x =1
φ (x) = 0.5 ,if x = 1
0.8 ,if x = i, i
-
-
0.2, if x =1
φ (x) = 0.5 ,if x = 1
0.7 ,if x = i, i
-
-
- -
- -
Clearly, +
µ = (µ ,µ )-
and +
φ = (φ ,φ )-
are bipolar anti-fuzzy subgroups of G.
8. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
8
Let us take p as follows p(x) = 0.2 for every x∈G, then the pseudo bipolar fuzzy cosets are,
p + +
0.08 ,if x =1
((aµ) ) (x) = p(a) µ (x)= 0.12 ,if x = 1
0.14 ,if x = i, i
-
-
p
0.06 ,if x =1
((aµ) ) (x) = p(a) µ (x) = 0.08 ,if x = 1
0.12 ,if x = i, i
- -
-
- -
- -
p + +
0.06 ,if x =1
((aφ) ) (x) = p(a) φ (x) = 0.10 ,if x = 1
0.16 ,if x = i, i
-
-
p
0.04 ,if x =1
((aφ) ) (x) = p(a) φ (x) = 0.1 ,if x = 1
0.14 ,if x = i, i
- -
-
- -
- -
Now the pseudo bipolar fuzzy double cosets are
p +
0.08 ,if x =1
((µaφ) ) (x) = 0.12 ,if x = 1
0.16 ,if x = i, i
-
-
p
0.06 ,if x =1
((µaφ) ) (x) = 0.1 ,if x = 1
0.14 ,if x = i, i
-
-
- -
- -
3.9 Theorem
If +
µ = (µ ,µ )-
be a bipolar fuzzy subgroup of a group G, then the pseudo bipolar fuzzy
coset (aµ)P
= (((aµ)P
)+
, ((aµ)P
)−
) is a bipolar fuzzy subgroup of a group G.
Proof:Let
+
µ = (µ ,µ )-
be a bipolar fuzzy subgroup of a group G.
For every x and y in G, we have,
i. ((aµ)P
)+
(xy −1
) = |p(a)| µ+
(xy−1
)
≥ |p(a)| min { µ+
(x), µ+
(y)}
= min {|p(a)| µ+
(x), |p(a)| µ+
(y)}
= min {((aµ)P
)+
(x), ((aµ)P
)+
(y)}
Therefore, ((aµ)P
)+
(xy −1
) ≥ min {((aµ)P
)+
(x), ((aµ)P
)+
(y)}
ii. ((aµ)P
)−
(xy −1
) = | p(a)| µ−
(xy −1
)
≤ | p(a)| max{ µ−
(x), µ−
(y)}
9. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
9
= max {| p(a)| µ−
(x), | p(a)| µ−
(y)}
= max {((aµ)P
)−
(x), ((aµ)P
)−
(y)}
Therefore, ((aµ)P
)−
(xy −1
) ≤ max{((aµ)P
)−
(x), ((aµ)P
)−
(y)}
Hence (aµ)P
is a bipolar fuzzy subgroup of a group G.
Note: (aµ)P
is called as a pseudo bipolar fuzzy subgroup of a group G if |p(a)| ≤ |p(e)| , for
every a∈G.
3.10 Theorem
If +
µ = (µ ,µ )-
be a bipolar anti-fuzzy subgroup of a group G, then the pseudo bipolar fuzzy
coset (aµ)P
= (((aµ)P
)+
, ((aµ)P
)−
) is a bipolar anti-fuzzy subgroup of a group G.
Proof:It is clear from the Theorem 3.9
Note: (aµ)P
is called as a pseudo bipolar anti-fuzzy subgroup of a group G if |p(a)| ≥
|p(e)|, for every a∈G.
3.11 Theorem
If +
µ = (µ ,µ )-
and +
φ = (φ ,φ )-
are two bipolar fuzzy subgroups of a group G, then the pseudo
bipolar fuzzy double coset (µaφ)P
= (((µaφ)P
)+
, ((µaφ)P
)−
) determined by µ and φ is also a bipolar
fuzzy subgroup of the group G.
Proof: For all x,y ∈ G,
i. ((µaφ)P
)+
(xy −1
) = {((aµ)P
∩ (aφ)P
) +
}(xy −1
)
= min { ((aµ)P
)+
(xy−1
) , ((aφ)P
)+
(xy−1
)}
= min { |p(a)| µ+
(xy−1
) , |p(a)| φ+
(xy−1
)}
= |p(a)| min { µ+
(xy−1
) , φ+
(xy−1
)}
≥ |p(a)| min {min { µ+
(x), µ+
(y)}, min{ φ+
(x), φ+
(y) }}
= |p(a)| min {min { µ+
(x) , φ+
(x)}, min{ µ+
(y) , φ+
(y)}}
= min{min{|p(a)| µ+
(x) , |p(a)| φ+
(x)}, min { |p(a)| µ+
(y), |p(a)| φ+
(y)}}
= min{min{((aµ)P
)+
(x),((aφ)P
)+
(x)},min{((aµ)P
)+
(y),((aφ)P
)+
(y)}}
= min {((aµ)P
∩ (aφ)P
) +
(x) , ((aµ)P
∩ (aφ)P
) +
(y)}
= min {(( µaφ)P
)+
(x) , ((µaφ)P
)+
(y) }
ii. ((µaφ)P
) −
( xy−1
) = {((aµ)P
∩ (aφ)P
) −
}( xy−1
)
= max { ((aµ)P
)−
(xy−1
) , ((aφ)P
)−
(xy−1
)}
= max { | p(a)| µ−
(xy−1
) , | p(a)| φ−
(xy−1
)}
= |p(a)| max { µ−
(xy−1
) , φ−
(xy−1
)}
≤ |p(a)| max {max { µ−
(x), µ−
(y)}, max{ φ−
(x), φ−
(y) }}
= |p(a)| max {max { µ−
(x), φ−
(x)}, max{ µ−
(y) , φ−
(y)}}
= max{max{|p(a)| µ−
(x) , |p(a)| φ−
(x)}, max{|p(a)| µ−
(y), |p(a)| φ−
(y)}}
10. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
10
= max {max{((aµ)P
)−
(x), ((aφ)P
)−
(x)}, max{((aµ)P
)−
(y), ((aφ)P
)−
(y)}}
= max {((aµ)P
∩ (aφ)P
) −
(x) , ((aµ)P
∩ (aφ)P
) −
(y)}
= max {(( µaφ)P
) −
(x) , ((µaφ)P
) −
(y) }
Hence, (µaφ)P
= (((µaφ)P
)+
, ((µaφ)P
)−
) is a bipolar fuzzy subgroup of the group G.
3.12 Theorem
If +
µ = (µ ,µ )-
and +
φ = (φ ,φ )-
are two bipolar anti-fuzzy subgroups of a group G, then the
pseudo bipolar fuzzy double coset (µaφ)P
= (((µaφ)P
)+
, ((µaφ)P
)−
) is also a bipolar anti- fuzzy
subgroup of the group G.
Proof: For all x,y ∈ G,
i. ((µaφ)P
)+
(xy −1
) = {((aµ)P
∩ (aφ)P
) +
}(xy −1
)
= max { ((aµ)P
)+
(xy−1
) , ((aφ)P
)+
(xy−1
)}
= max { |p(a)| µ+
(xy−1
) , |p(a)| φ+
(xy−1
)}
= |p(a)| max { µ+
(xy−1
) , φ+
(xy−1
)}
≤ |p(a)| max {max { µ+
(x), µ+
(y)}, max{ φ+
(x), φ+
(y) }}
= |p(a)| max {max { µ+
(x) , φ+
(x)}, max{ µ+
(y) , φ+
(y)}}
= max{max{|p(a)| µ+
(x), |p(a)| φ+
(x)},max { |p(a)| µ+
(y), |p(a)| φ+
(y)}}
= max{max{((aµ)P
)+
(x),((aφ)P
)+
(x)},max{((aµ)P
)+
(y),((aφ)P
)+
(y)}}
= max {((aµ)P
∩ (aφ)P
) +
(x) , ((aµ)P
∩ (aφ)P
) +
(y)}
= max {(( µaφ)P
)+
(x) , ((µaφ)P
)+
(y) }
ii. ((µaφ)P
) −
( xy−1
) = {((aµ)P
∩ (aφ)P
) −
}( xy−1
)
= min { ((aµ)P
)−
(xy−1
) , ((aφ)P
)−
(xy−1
)}
= min { |p(a)| µ−
(xy−1
) , |p(a)| φ−
(xy−1
)}
= |p(a)| min { µ−
(xy−1
) , φ−
(xy−1
)}
≥ |p(a)| min {min { µ−
(x), µ−
(y)}, min{ φ−
(x), φ−
(y) }}
= |p(a)| min {min { µ−
(x), φ−
(x)}, min{ µ−
(y) , φ−
(y)}}
= min{min{|p(a)| µ−
(x) , |p(a)| φ−
(x)}, min{|p(a)| µ−
(y), |p(a)| φ−
(y)}}
= min {min{((aµ)P
)−
(x), ((aφ)P
)−
(x)}, min {((aµ)P
)−
(y), ((aφ)P
)−
(y)}}
= min {((aµ)P
∩ (aφ)P
) −
(x) , ((aµ)P
∩ (aφ)P
) −
(y)}
= min {((µaφ)P
) −
(x) , ((µaφ)P
) −
(y) }
Hence, (µaφ)P
= (((µaφ)P
)+
, ((µaφ)P
)−
) is a bipolar anti-fuzzy subgroup of the group G.
4. Pseudo bipolar fuzzy cosets and Pseudo bipolar fuzzy double cosets of
bipolar fuzzy and bipolar anti-fuzzy HX subgroups and their
properties:
In this section, we define the concepts of pseudo bipolar fuzzy cosets, pseudo bipolar fuzzy
double cosets of a bipolar fuzzy and bipolar anti-fuzzy HX subgroups of a HX group and discuss
some of their properties.
11. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
11
4.1 Definition [2]
Let G be a finite group. In 2G
−{φ}, a nonempty set ϑ ⊂ 2G
−{φ} is called a HX group on G, if
ϑ is a group with respect to the algebraic operation defined by AB = { ab /a
∈ A and b ∈ B}, which its unit element is denoted by E.
4.2 Definition [9]
Let ϑ be a non-empty set. A bipolar-valued fuzzy set or bipolar fuzzy set λµ in ϑ is an
object having the form λµ = {〈A, λµ
+
(A), λµ
−
(A)〉 : A ∈ ϑ} where λµ
+
: ϑ → [0,1] and λµ
−
: ϑ →
[−1,0] are mappings. The positive membership degree λµ
+
(A) denotes the satisfaction degree of
an element A to the property corresponding to a bipolar-valued fuzzy set λµ = {〈A, λµ
+
(A),
λµ
−
(A)〉: A ∈ ϑ } and the negative membership degree λµ
−
(A) denotes the satisfaction degree of an
element A to some implicit counter property corresponding to a bipolar-valued fuzzy set λµ
={〈A, λµ
+
(A), λµ
−
(A)〉: A ∈ ϑ}. If λµ
+
(A) ≠ 0 and λµ
−
(A) = 0, it is the situation that A is
regarded as having only positive satisfaction for λµ = {〈A, λµ
+
(A), λµ
−
(A)〉: A ∈ ϑ}. If λµ
+
(A)
= 0 and λµ
−
(A) ≠ 0, it is the situation that A does not satisfy the property of λµ = {〈A,
λµ
+
(A), λµ
−
(A)〉 : A ∈ ϑ} , but somewhat satisfies the counter property of λµ = {〈A, λµ
+
(A),
λµ
−
(A)〉: A∈ϑ}. It is possible for an element A to be such that λµ
+
(A) ≠ 0 and λµ
−
(A) ≠ 0
when the membership function of property overlaps that its counter property over some
portion of ϑ. For the sake of simplicity, we shall use the symbol λµ = ( λµ
+
, λµ
−
) for the
bipolar-valued fuzzy set λµ = {〈A, λµ
+
(A), λµ
−
(A)〉: A ∈ ϑ}.
4.3 Definition [9]
Let +
µ = (µ ,µ )-
be a bipolar fuzzy subset defined on G. Let ϑ ⊂ 2G
−{φ} be a HX group of G.
A bipolar fuzzy set λµ = (λµ
+
, λµ
−
) defined on ϑ is said to be a bipolar fuzzy subgroup
induced by µ on ϑ or a bipolar fuzzy HX subgroup of ϑ if for A,B ∈ϑ,
i.λµ
+
(AB) ≥ min{ λµ
+
(A), λµ
+
(B)}
ii.λµ
−
(AB) ≤ max{ λµ
−
(A), λµ
−
(B)}
iii.λµ
+
(A−1
) = λµ
+
(A) , λµ
−
(A−1
) = λµ
−
(A).
Where λµ
+
(A) = max {µ+
(x) / for all x ∈ A ⊆ G} and
λµ
−
(A) = min {µ−
(x) / for all x ∈ A ⊆ G}.
Remark [9]
i. If µ is a bipolar fuzzy subgroup of G then the bipolar fuzzy subset λµ = (λµ
+
, λµ
−
) is a fuzzy
HX subgroup on ϑ.
ii. Let µ be a bipolar fuzzy subset of a group G. If λµ = (λµ
+
, λµ
−
) is a bipolar fuzzy HX subgroup
on ϑ, then µ need not be a bipolar fuzzy subgroup of G.
4.4 Definition [9]
Let +
µ = (µ ,µ )-
be a bipolar fuzzy subset defined on G. Let ϑ ⊂ 2G
−{φ} be a HX group of
G. A bipolar fuzzy set λµ = (λµ
+
, λµ
−
) defined on ϑ is said to be a bipolar anti- fuzzy subgroup
induced by µ on ϑ or a bipolar anti-fuzzy HX subgroup of ϑ if for A, B∈ϑ,
12. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
12
i.λµ
+
(AB) ≤ max { λµ
+
(A), λµ
+
(B)}
ii.λµ
−
(AB) ≥ min { λµ
−
(A), λµ
−
(B)}
iii.λµ
+
(A−1
) = λµ
+
(A) , λµ
−
(A−1
) = λµ
−
(A).
Where λµ
+
(A) = min {µ+
(x) / for all x ∈ A ⊆ G} and
λµ
−
(A) = max{µ−
(x) / for all x ∈ A ⊆ G}
Remark [7]
1.If +
µ = (µ ,µ )-
is a bipolar anti-fuzzy subgroup of G then λµ = (λµ
+
, λµ
−
) is a bipolar anti-
fuzzy HX subgroup on ϑ.
2.Let +
µ = (µ ,µ )-
be a bipolar fuzzy subset of a group G. If λµ = (λµ
+
, λµ
−
) is a bipolar anti-
fuzzy HX subgroup on ϑ,then +
µ = (µ ,µ )-
need not be a bipolar anti-fuzzy subgroup of G.
4.5 Definition
Let λµ = (λµ
+
,λµ
−
) be a bipolar fuzzy HX subgroup of a HX group ϑ and A ∈ ϑ. Then the pseudo
bipolar fuzzy coset (Aλµ)P
= (((Aλµ)P
)+
, ((Aλµ)P
)−
) is defined by
i.((Aλµ)P
)+
(X) = |p(A)| λµ
+
(X)
ii.((Aλµ)P
) −
(X) = |p(A)| λµ
−
(X).For every X ∈ ϑ and
iii.
for some p∈ P Where P = {p(X) / p(X) ∈ [−1,1] and p(X) ≠ 0 for all X∈ϑ}.
4.6 Example
Let G ={1, 1,i, i}- - be a group under the binary operation multiplication. Define a bipolar
fuzzy subset +
µ = (µ ,µ )-
on G as,
+
0.8 ,if x =1
µ (x) = 0.7 ,if x = 1
0.5 ,if x = i, i
-
-
0.7 , if x =1
µ (x) = 0.6 ,if x = 1
0.4 ,if x = i, i
-
-
- -
- -
Clearly
+
µ = (µ ,µ )-
is a bipolar fuzzy subgroup of G.
Let ϑ = {{1, −1},{i, −i}} = { E,A } , where E = {1, −1} , A = {i, −i} .Clearly (ϑ, ⋅) is a HX
group. Let λµ = (λµ
+
,λµ
−
) be a bipolar fuzzy subset on ϑ induced by +
µ = (µ ,µ )-
on G is,
+
µ
0.8 ,if X = E
λ (X) =
0.5 ,if X = A
µ
0.7 , if X = E
λ (X) =
0.4 ,if X = A
-
-
-
13. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
13
Let us take p as follows:
0.5 ,if X = E
p(X) =
0.66 ,if X = A
the pseudo bipolar fuzzy cosets are,
i.
p +
µ((Eλ ) ) (X) = +
µ
0.40 ,if X = E
p(E) λ (X) =
0.25 ,if X = A
p
µ((Eλ ) ) (X) =-
µ
0.35 ,if X = E
p(E) λ (X) =
0.20 ,if X = A
- -
-
ii.
p +
µ((Aλ ) ) (X) = +
µ
0.528 ,if X = E
p(A) λ (X) =
0.132 ,if X = A
p
µ((Aλ ) ) (X) =-
µ
0.452 ,if X = E
p(A) λ (X) =
0.264 ,if X = A
-
-
-
Note: If p(X) = 1± , for all X∈ϑ, then (X λµ) p
= λµ .
4.7 Definition
Let λµ = (λµ
+
,λµ
−
) be a bipolar anti-fuzzy HX subgroup of a HX group ϑ and let A ∈ ϑ. Then
the pseudo bipolar fuzzy coset (Aλµ)P
= (((Aλµ)P
)+
, ((Aλµ)P
)−
) is defined by
i.((Aλµ)P
)+
(X) = |p(A)| λµ
+
(X)
ii.((Aλµ)P
) −
(X) = | p(A)| λµ
−
(X)
iii.
for every X ∈ ϑ and for some p∈ P, Where P = { p(X) / p(X) ∈ [−1,1] and p(X) ≠ 0 for all
X∈ϑ}.
4.8 Example
Let G = { e,a,b,ab } be a group under the binary operation multiplication. Where a2
= e = b2
, ab =
ba and e is the identity element of G .Define a bipolar fuzzy subset µ = (µ+
,µ−
) on G as,
+
0.4 ,if x = e
µ (x) = 0.5 ,if x = a
0.8 ,if x = b,ab
0.5 , if x = e
µ (x) = 0.6 ,if x = a
0.7 ,if x = b,ab
-
-
-
-
Clearly +
µ = (µ ,µ )-
is a bipolar anti fuzzy subgroup of G.
Let ϑ = {{e,a},{b,ab}} = { E,A } , where E = {e,a} , A = {b,ab} .Clearly (ϑ, ⋅) is a HX group.
14. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
14
Let λµ = (λµ
+
,λµ
−
) be a bipolar fuzzy subset on ϑ induced by µ = (µ+
,µ−
) on G is,
+
µ
0.4 ,if X = E
λ (X) =
0.8 ,if X = A
µ
0.5 , if X = E
λ (X) =
0.7 ,if X = A
- -
-
Let us take p as follows:
0.6 ,if X = E
p(X) =
0.5 ,if X = A
the pseudo bipolar fuzzy cosets are,
i.
p +
µ((Eλ ) ) (X) = +
µ
0.24 ,if X = E
p(E) λ (X) =
0.48 ,if X = A
p
µ((Eλ ) ) (X) =-
µ
0.3 ,if X = E
p(E) λ (X) =
0.42 ,if X = A
- -
-
ii.
p +
µ((Aλ ) ) (X) = +
µ
0.2 ,if X = E
p(A) λ (X) =
0.4 ,if X = A
p
µ((Aλ ) ) (X) =-
µ
0.25 ,if X = E
p(A) λ (X) =
0.35 ,if X = A
-
-
-
Note: If p(X) = 1± and p(X) 0≠ , for all X∈ϑ, then (X λµ) p
= λµ .
4.9 Definition
Let λµ = (λµ
+
, λµ
−
) and σφ = (σφ
+
, σφ
−
) be any two bipolar fuzzy HX subgroups of a HX group ϑ,
then pseudo bipolar fuzzy double coset (λµAσφ)P
= (((λµAσφ)P
)+,
((λµAσφ)P
)−
) is defined by
i.((λµAσφ)P
)+
(X) = ((Aλµ)P
∩ (Aσφ)P
)+
(X) = min{((Aλµ)P
)+
(X) , ((Aσφ)P
)+
(X) }
ii.((λµAσφ)P
)−
(X) = ((Aλµ)P
∩ (Aσφ)P
)−
(X) = max{((Aλµ)P
)−
(X), ((Aσφ)P
)−
(X)}
for every X ∈ ϑ and for some p∈ P , Where P = {p(X) / p(X) ∈ [−1,1] , p(X) ≠ 0 for all X∈ϑ}.
4.10 Example
Let G ={1, 1,i, i}- - be a group under the binary operation multiplication. Define a bipolar
fuzzy subsets
+
µ = (µ ,µ )-
and
+
φ = (φ ,φ )-
on G as,
+
0.8 ,if x =1
µ (x) = 0.6 ,if x = 1
0.3 ,if x = i, i
-
-
0.6 , if x =1
µ (x) = 0.4 ,if x = 1
0.2 ,if x = i, i
-
-
- -
- -
15. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
15
+
0.9 ,if x =1
φ (x) = 0.5 ,if x = 1
0.2 ,if x = i, i
-
-
0.8 , if x =1
φ (x) = 0.6 ,if x = 1
0.1 ,if x = i, i
-
-
- -
- -
and let ϑ = {{1, −1},{i, −i}} = {E,A} , where E = {1, −1} , A = {i, −i}.Clearly (ϑ, ⋅) is a HX
group. Let λµ = (λµ
+
, λµ
−
) and σφ = (σφ
+
, σφ
−
) are bipolar fuzzy subsets on ϑ induced by
+
µ = (µ ,µ )-
and +
φ = (φ ,φ )-
on G are
+
µ
0.8 ,if X = E
λ (X) =
0.3 ,if X = A
µ
0.6 , if X = E
λ (X) =
0.2 ,if X = A
-
-
-
+
φ
0.9 ,if X = E
σ (X) =
0.2 ,if X = A
φ
0.8 , if X = E
σ (X) =
0.1 ,if X = A
- -
-
Then the pseudo fuzzy cosets (Aλµ)p
and (Aσφ)p
for p (X) = − 0.4 , for every X ∈ ϑ is
i.
p +
µ((Aλ ) ) (X) = +
µ
0.32 ,if X = E
p(A) λ (X) =
0.12 ,if X = A
p
µ((Aλ ) ) (X) =-
µ
0.24 ,if X = E
p(A) λ (X) =
0.08 ,if X = A
- -
-
ii.
p +
φ((Aσ ) ) (X) = +
φ
0.36 ,if X = E
p(A) σ (X) =
0.08 ,if X = A
p
φ((Aσ ) ) (X) =-
φ
0.32 ,if X = E
p(A) σ (X) =
0.04 ,if X = A
-
-
-
and Now the pseudo bipolar fuzzy double coset determined by λµ and σφ is given by
( )( )
+p
µ φ
0.32 ,if X = E
λ Aσ (X) =
0.08 ,if X = A
, ( )( )p
µ φ
0.24 ,if X = E
λ Aσ (X) =
0.04 ,if X = A
- -
-
Note:
16. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
16
Similarly we can define pseudo bipolar fuzzy double cosets on a bipolar anti-fuzzy HX subgroup
of a HX group.
4.11 Theorem
If λµ = (λµ
+
, λµ
−
) be a bipolar fuzzy HX subgroup of a HX group ϑ, then the pseudo bipolar
fuzzy coset (Aλµ)P
= (((Aλµ)P
)+
, ((Aλµ)P
)−
) is a bipolar fuzzy HX subgroup of a HX group ϑ.
Proof:Let λµ = (λµ
+
, λµ
−
) be a bipolar fuzzy HX subgroup of a HX group ϑ.
For every X and Y in ϑ, we have,
i. ((Aλµ)P
)+
(XY−1
) = |p(A)| λµ
+
(XY−1
)
≥ |p(A)| min { λµ
+
(X), λµ
+
(Y)}
= min { |p(A)| λµ
+
(X), |p(A)| λµ
+
(Y)}
= min {((Aλµ)P
)+
(X), ((Aλµ)P
)+
(Y)}
Therefore, ((Aλµ)P
)+
(XY-1
) ≥ min {((Aλµ)P
)+
(X), ((Aλµ)P
)+
(Y)}
ii. ((Aλµ)P
)−
(XY−1
) = |p(A)| λµ
−
(XY−1
)
≤ |p(A)| max{ λµ
−
(X), λµ
−
(Y)}
= max {|p(A)| λµ
−
(X), |p(A)| λµ
−
(Y)}
= max {((Aλµ)P
)−
(X), ((Aλµ)P
)−
(Y)}
Therefore, ((Aλµ)P
)−
(XY−1
) ≤ max{((Aλµ)P
)−
(X), ((Aλµ)P
)−
(Y)}
Hence (Aλµ)P
is a bipolar fuzzy HX subgroup of a HX group ϑ.
Note: (Aλµ)P
is called as a pseudo bipolar fuzzy HX subgroup of ϑ if |p(A)| ≤ |p(E)| for every A
∈ ϑ.
4.12 Theorem
If λµ = (λµ
+
, λµ
−
) be a bipolar anti-fuzzy HX subgroup of a HX group ϑ, then the pseudo
bipolar fuzzy coset (Aλµ)P
is also a bipolar anti-fuzzy HX subgroup of a HX group ϑ.
Proof: it is clear from Theorem 4.11.
Note: (Aλµ)P
is also called as pseudo bipolar anti-fuzzy HX subgroup of ϑ if |p(A)| ≥ |p(E)| for
every A ∈ ϑ.
4.13 Theorem
If λµ = (λµ
+
, λµ
−
) and σφ = (σφ
+
, σφ
−
) are two bipolar fuzzy HX subgroups of a HX group ϑ, then
the pseudo bipolar fuzzy double coset (λµAσφ)P
= (((λµAσφ)P
)+
, ((λµAσφ)P
)−
) determined by λµ
and σφ is also a bipolar fuzzy HX subgroup of the HX group ϑ.
Proof: For all X, Y ∈ ϑ,
i. ((λµAσφ)P
)+
(XY−1
) = {((Aλµ)P
∩ (Aσφ)P
) +
}(XY−1
)
20. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
20
ii. ((Aλµ)P
∩ (Aσφ)P
) −
(XY−1
) = min {((Aλµ)P
)−
(XY−1
) , ((Aσφ)P
)−
(XY−1
) }
= min { |p(A)| λµ
−
(XY−1
), | p(A)| σφ
−
(XY−1
)}
= |p(A)| min{ λµ
−
(XY−1
), σφ
−
( XY−1
)}
≥ |p(A)| min{min{ λµ
−
(X), λµ
−
(Y)}, min{ σφ
−
(X), σφ
−
(Y)}}
= |p(A)| min{min{ λµ
−
(X), σφ
−
(X)}, min{ λµ
−
(Y), σφ
−
(Y)}}
= min{|p(A)|{ min{λµ
−
(X), σφ
−
(X)}, min{ λµ
−
(Y), σφ
−
(Y)}}}
= min{min{|p(A)| λµ
−
(X) , |p(A)| σφ
−
(X)},min{|p(A)| λµ
−
(Y) , |p(A)| σφ
−
(Y)}}
= min{min{((Aλµ)P
)−
(X), ((Aσφ)P
)−
(X)},min {((Aλµ)P
)−
(Y), ((Aσφ)P
)−
(Y)}}
= min{((Aλµ)P
∪ (Aσφ)P
) −
(X) , ((Aλµ)P
∪ (Aσφ)P
) −
(Y)}}
Hence the Union of any two pseudo bipolar anti-fuzzy HX subgroups of a HX group ϑ is also a
pseudo bipolar anti-fuzzy HX subgroup of ϑ.
4.18 Theorem
Union of any two pseudo bipolar fuzzy HX subgroup of a HX group ϑ is also a pseudo bipolar
fuzzy HX subgroup of ϑ.
Proof: Let (Aλµ)P
= (((Aλµ)P
)+
, ((Aλµ)P
)−
) and (Aσφ)P
= (((Aσφ)P
)+
, ((Aσφ)P
)−
) be any two
pseudo bipolar fuzzy HX subgroups of a HX group ϑ.
Now, Union of any two pseudo bipolar fuzzy HX subgroup on a HX subgroup ϑ is
((Aλµ)P
∪ (Aσφ)P
) = (((Aλµ)P
∪ (Aσφ)P
) +
, ((Aλµ)P
∪ (Aσφ)P
)−
)
i. ((Aλµ)P
∪(Aσφ)P
) +
(XY−1
) = max {((Aλµ)P
)+
(XY−1
) , ((Aσφ)P
)+
(XY−1
) }
= max { |p(A)| λµ
+
(XY−1
), |p(A)| σφ
+
(XY−1
)}
= |p(A)| max{ λµ
+
(XY−1
), σφ
+
( XY−1
)}
≥ |p(A)| max{min{ λµ
+
(X), λµ
+
(Y)}, min{ σφ
+
(X), σφ
+
(Y)}}
= |p(A)| min{max{ λµ
+
(X), σφ
+
(X)}, max{ λµ
+
(Y), σφ
+
(Y)}}
= min{ |p(A)|{max{ λµ
+
(X), σφ
+
(X)}, max{ λµ
+
(Y), σφ
+
(Y)}}}
= min{max{ |p(A)| λµ
+
(X) , |p(A)| σφ
+
(X)}, max{ |p(A)| λµ
+
(Y) , |p(A)| σφ
+
(Y)}}
= min{max{((Aλµ)P
)+
(X), ((Aσφ)P
)+
(X)},max {((Aλµ)P
)+
(Y), ((Aσφ)P
)+
(Y)}}
= min{((Aλµ)P
∪ (Aσφ)P
) +
(X) , ((Aλµ)P
∪ (Aσφ)P
) +
(Y)}}
ii. ((Aλµ)P
∩ (Aσφ)P
) −
(XY−1
) = min {((Aλµ)P
)−
(XY−1
) , ((Aσφ)P
)−
(XY−1
) }
= min { |p(A)| λµ
−
(XY−1
) , |p(A)| σφ
−
(XY−1
)}
= |p(A)| min{ λµ
−
(XY−1
), σφ
−
( XY−1
)}
≤ |p(A)| min{max{λµ
−
(X), λµ
−
(Y)}, max{σφ
−
(X), σφ
−
(Y)}}
= |p(A)| max{min{ λµ
−
(X), σφ
−
(X)}, min{ λµ
−
(Y), σφ
−
(Y)}}
= max{ |p(A)|{min{λµ
−
(X), σφ
−
(X)}, min{λµ
−
(Y), σφ
−
(Y)}}}
= max{min{|p(A)| λµ
−
(X) , |p(A)| σφ
−
(X)}, min{|p(A)| λµ
−
(Y) , |p(A)| σφ
−
(Y)}}
= max{min{((Aλµ)P
)−
(X), ((Aσφ)P
)−
(X)},min {((Aλµ)P
)−
(Y), ((Aσφ)P
)−
(Y)}}
= max{((Aλµ)P
∪ (Aσφ)P
) −
(X) , ((Aλµ)P
∪ (Aσφ)P
) −
(Y)}}
Hence the Union of any two pseudo bipolar fuzzy HX subgroups of a HX group ϑ is also a
pseudo bipolar fuzzy HX subgroup of ϑ.
21. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
21
CONCLUSIONS
We have given the notion of the pseudo bipolar fuzzy cosets and pseudo bipolar fuzzy cosets of
bipolar fuzzy HX subgroup and bipolar anti-fuzzy HX subgroup of a HX group. The union and
intersection of pseudo bipolar fuzzy HX subgroups and pseudo bipolar anti-fuzzy HX subgroups
of a HX group are discussed. We hope that our results can also be extended to other algebraic
system.
ACKNOWLEDGEMENTS
The authors are highly grateful to the referees for their constructive suggestions for improving the
paper.
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Authors
Dr.R.Muthuraj received his Ph.D degree in Mathematics from Alagappa University
Karaikudi, Tamilnadu,India in April 2010.Presently he is an Assistant Professor , PG
22. Applied Mathematics and Sciences: An International Journal (MathSJ ), Vol. 1, No. 3, December 2014
22
& Research Department of Mathematics, H.H.The Rajah’s College, Pudukkottai – 622 001, Tamilnadu
,India. He has published over 80 papers in refereed national and International Journals.He is the reviewer
and Editor of the reputed International Journals. Eight members are doing research work under his
guidance. His research interests are Fuzzy Algebra, Lattice Theory, Discrete Mathematics, Fuzzy Topology
and Fuzzy Graph Theory.
M.Sridharan received his M.Phil degree from School of Mathematics, Madurai
Kamaraj University,Madurai, Tamilnadu,India. Now he is doing Ph.D from
Bharathidasan University Tiruchirappalli,Tamilnadu,India. Presently he is working as
an Associate Professor of Mathematics , PSNA College of Engineering and
Technology, Dindigul,Tamilnadu, India. He has published over 18 papers in reputed
national and International journals. His research area is
Fuzzy Algebra.