mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...

, the membership function of a fuzzy set is a generalization of the

indicator function In mathematics, an indicator function or a characteristic function of a subset of a set is a function that maps elements of the subset to one, and all other elements to zero. That is, if is a subset of some set , one has \mathbf_(x)=1 if x\i ...

for classical sets. In

fuzzy logic Fuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completel ...

, it represents the degree of truth as an extension of valuation. Degrees of truth are often confused with

probabilities Probability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur, or how likely it is that a proposition is true. The probability of an event is a number between 0 and 1, where, roughly speaking, ...

, although they are conceptually distinct, because fuzzy truth represents membership in vaguely defined sets, not likelihood of some event or condition. Membership functions were introduced by Aliasker Zadeh in the first paper on fuzzy sets (1965). Aliasker Zadeh, in his theory of fuzzy sets, proposed using a membership function (with a range covering the interval (0,1)) operating on the domain of all possible values.

Definition

For any set

X

, a membership function on

X

is any function from

X

to the real

unit interval In mathematics, the unit interval is the closed interval , that is, the set of all real numbers that are greater than or equal to 0 and less than or equal to 1. It is often denoted ' (capital letter ). In addition to its role in real analysis ...

,1 /math>.

Membership functions represent fuzzy subsets of X . The membership function which represents a fuzzy set \tilde A is usually denoted by \mu_A. For an element x of X, the value \mu_A(x) is called the ''membership degree'' of x in the fuzzy set \tilde A. The membership degree \mu_(x) quantifies the grade of membership of the element x to the fuzzy set \tilde A. The value 0 means that x is not a member of the fuzzy set; the value 1 means that x is fully a member of the fuzzy set. The values between 0 and 1 characterize fuzzy members, which belong to the fuzzy set only partially.

Sometimes,First in Goguen (1967). a more general definition is used, where membership functions take values in an arbitrary fixed

algebra Algebra () is one of the broad areas of mathematics. Roughly speaking, algebra is the study of mathematical symbols and the rules for manipulating these symbols in formulas; it is a unifying thread of almost all of mathematics. Elementary ...

structure A structure is an arrangement and organization of interrelated elements in a material object or system, or the object or system so organized. Material structures include man-made objects such as buildings and machines and natural objects such a ...

L

; usually it is required that

L

be at least a

poset In mathematics, especially order theory, a partially ordered set (also poset) formalizes and generalizes the intuitive concept of an ordering, sequencing, or arrangement of the elements of a set. A poset consists of a set together with a binary r ...

or lattice. The usual membership functions with values in , 1are then called , 1valued membership functions.

Capacity

''See the article on

Capacity of a set In mathematics, the capacity of a set in Euclidean space is a measure of the "size" of that set. Unlike, say, Lebesgue measure, which measures a set's volume or physical extent, capacity is a mathematical analogue of a set's ability to hold electr ...

for a closely related definition in mathematics.'' One application of membership functions is as capacities in

decision theory Decision theory (or the theory of choice; not to be confused with choice theory) is a branch of applied probability theory concerned with the theory of making decisions based on assigning probabilities to various factors and assigning numerical ...

. In

, a capacity is defined as a function,

\nu

from S, the set of

subset In mathematics, set ''A'' is a subset of a set ''B'' if all elements of ''A'' are also elements of ''B''; ''B'' is then a superset of ''A''. It is possible for ''A'' and ''B'' to be equal; if they are unequal, then ''A'' is a proper subset of ...

s of some set, into

,1 /math>, such that \nu is set-wise monotone and is normalized (i.e. \nu(\empty) = 0, \nu(\Omega)=1). This is a generalization of the notion of a

probability measure In mathematics, a probability measure is a real-valued function defined on a set of events in a probability space that satisfies measure properties such as ''countable additivity''. The difference between a probability measure and the more ge ...

, where the probability axiom of countable additivity is weakened. A capacity is used as a subjective measure of the likelihood of an event, and the "

expected value In probability theory, the expected value (also called expectation, expectancy, mathematical expectation, mean, average, or first moment) is a generalization of the weighted average. Informally, the expected value is the arithmetic mean of a ...

" of an outcome given a certain capacity can be found by taking the Choquet integral over the capacity.

References

{{reflist

Bibliography

*Zadeh L.A., 1965, "Fuzzy sets". ''Information and Control'' 8: 338–353

*Goguen J.A, 1967, "''L''-fuzzy sets". ''Journal of Mathematical Analysis and Applications'' 18: 145–174

External links

Fuzzy Image Processing
Fuzzy logic

Definition

Capacity

See also

References

Bibliography

External links