Difference between revisions of "Function"
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==Rigorous Definition== | ==Rigorous Definition== | ||
− | Let <math>A</math>,<math>B</math> be [[set]]s and let <math>f | + | Let <math>A</math>,<math>B</math> be [[set]]s and let <math>f</math> be a [[subset]] of <math>A\times B</math>, which denotes the [[Cartesian product]] of <math>A</math> and <math>B</math>. (That is, <math>f</math> is a [[relation]] between <math>A</math> and <math>B</math>.) We say that <math>f</math> is a ''function from <math>A</math> to <math>B</math>'' (written <math>f: A \to B</math>) if and only if |
* For every <math>a \in A</math> there is some <math>b \in B</math> such that <math>(a, b) \in f</math>, and | * For every <math>a \in A</math> there is some <math>b \in B</math> such that <math>(a, b) \in f</math>, and | ||
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==Introductory Topics== | ==Introductory Topics== | ||
===Domain and Range=== | ===Domain and Range=== | ||
− | The domain of a function is the [[set]] of input values for the argument of a function. The range of a function is the [[set]] of output values for that function. For an example, consider the function: <math>f(x) = \sqrt{x^2-9}</math>. The domain of the function is the set <math>{x:|x| | + | The ''domain'' of a function is the [[set]] of input values for the argument of a function. The ''range'' of a function is the [[set]] of output values for that function. For an example, consider the function: <math>f(x) = \sqrt{x^2-9}</math>. The domain of the function is the set <math>\{x:|x| \geq 3\}</math>, where <math>x</math> is a real number, because the square root is only defined when its argument is nonnegative. The range is the set of all non-negative real numbers, because the square root can never return a negative value. |
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===Real Functions=== | ===Real Functions=== | ||
− | A real function is a function whose [[range]] is in the real numbers. Usually we speak about | + | A real function is a function whose [[range]] is in the real numbers. Usually we speak about functions whose domain is also a [[subset]] of the real numbers. |
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===Graphs=== | ===Graphs=== | ||
− | + | Functions are often graphed. A graph corresponds to a function only if it stands up to the [[vertical line test]]. | |
− | Functions are often graphed. | ||
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===Inverses=== | ===Inverses=== | ||
+ | The inverse of a function is a function that "undoes" a function. For an example, consider the function: <math>f(x) = x^2 + 6</math>. The function <math>g(x) = \sqrt{x-6}</math> has the property that <math>f(g(x)) = x</math>. Therefore, <math>g</math> is called the '''(right) inverse function'''. (Similarly, a function <math>g</math> that satisfies <math>g(f(x))=x</math> is called the '''left inverse function'''. Typically the right and left inverses coincide on a suitable domain, and in this case we simply call the right and left inverse function the '''inverse function'''.) Often the inverse of a function <math>f</math> is denoted by <math>f^{-1}</math>. | ||
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==Intermediate Topics== | ==Intermediate Topics== | ||
===Injections, Surjections, Bijections=== | ===Injections, Surjections, Bijections=== | ||
− | *An [[injection]] (or one-to-one function) is a function which | + | *An [[injection]] (or one-to-one function) is a function which always gives distinct values for distinct arguments within a given domain. |
− | + | **By definition, <math>f:A\to B</math> is injective if <math>f(a)=f(b) \Rightarrow a=b </math>, or equivalently, <math>a\neq b \Rightarrow f(a)\neq f(b).</math> | |
− | By definition, <math>f:A\to B</math> is injective if <math>f(a)=f(b) \Rightarrow a=b </math>, or equivalently, <math>a\neq b \Rightarrow f(a)\neq f(b).</math> | + | **Injectivity of a function <math>f: A \rightarrow B</math> implies that <math>f</math> has an inverse. Furthermore, if <math>A</math> and <math>B</math> are finite sets, injectivity implies <math>|A|\leq |B|</math>. |
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− | Injectivity of a function <math>f: A \rightarrow B</math> implies that <math>f</math> has an inverse. Furthermore, if <math>A</math> and <math>B</math> are finite sets, injectivity implies <math>|A|\leq |B|</math>. | ||
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*A [[surjection]] (or onto function) maps at least one element from its domain, <math>A,</math> onto every element of its range, <math>B.</math> | *A [[surjection]] (or onto function) maps at least one element from its domain, <math>A,</math> onto every element of its range, <math>B.</math> | ||
+ | *A [[bijection]] (or one-to-one correspondence, which must be one-to-one and onto) is a function, <math>f: A \rightarrow B</math> that is both injective and surjective. | ||
+ | **If <math>f</math> is an injection from <math>A \rightarrow B</math> and <math>g</math> is an injection from <math>B \rightarrow A,</math> then there exists a bijection, <math>h,</math> between <math>A</math> and <math>B</math>. This is the [[Schroeder-Bernstein Theorem]]. | ||
− | Examples | + | ====Examples==== |
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− | * | + | * <math>f(x) = x</math> is injective and surjective (and therefore bijective) from <math>\mathbb{C} \rightarrow \mathbb{C}</math>. |
− | + | * <math>f(x) = x^2</math> is injective from <math>\mathbb{R^+} \rightarrow \mathbb{R}</math>. | |
− | + | * <math>f(x) = x^2</math> is surjective from <math>\mathbb{R} \rightarrow \mathbb{R^+}</math>. | |
+ | * <math>f(x) = x^2</math> is neither injective from <math>\mathbb{R} \rightarrow \mathbb{R}</math> (since <math>f(2) = 4 = f(-2)</math>) nor surjective from <math>\mathbb{R} \rightarrow \mathbb{R}</math> (since <math>f</math> does not map any value to <math>-5</math>, which is an element of <math>\mathbb{R}</math>). | ||
===Monotonic functions=== | ===Monotonic functions=== | ||
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===Continuity=== | ===Continuity=== | ||
− | Intuitively, a continuous function has the propriety that its graph can be drawn without taking the pencil off the paper. | + | Intuitively, a continuous function has the propriety that its graph can be drawn without taking the pencil off the paper. To rigorously define continuous functions, more complex mathematics is necessary. |
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====Epsilon-Delta Definition==== | ====Epsilon-Delta Definition==== | ||
− | A function <math>f:E\to\mathbb{R}</math> is called continuous at <math> x_{0} </math> if, for all <math> \varepsilon >0 </math>, there exists <math>\delta >0</math> such that <math> |x-x_0|<\delta </math> | + | A function <math>f:E\to\mathbb{R}</math> is called ''continuous'' at some point in its domain <math> x_{0} </math> if, for all <math> \varepsilon >0 </math>, there exists <math>\delta >0</math> such that, for any <math>x \in E</math>, the condition <math> |x-x_0|<\delta </math> implies that <math>|f(x)-f(x_0)|<\varepsilon </math>. |
====Heine Definition==== | ====Heine Definition==== | ||
The previous definition of continuity at <math> x_{0} </math> is equivalent with the following: for every sequence <math> (x_n)_{n\geq 0} </math> such that <math>\lim_{n\to\infty}x_n=x_0 </math>, we have that <math> \lim_{n\to\infty}f(x_n)=f(x_0) </math>. | The previous definition of continuity at <math> x_{0} </math> is equivalent with the following: for every sequence <math> (x_n)_{n\geq 0} </math> such that <math>\lim_{n\to\infty}x_n=x_0 </math>, we have that <math> \lim_{n\to\infty}f(x_n)=f(x_0) </math>. | ||
− | It is easy to see that a function is continuous in [[isolated point]]s, and is continuous in [[ | + | It is easy to see that a function is continuous in [[isolated point]]s, and is continuous in large groups of points [[if]] the limit of the function in those points equals the value of the function. |
A function is continuous on a set if it is continuous in every point of the set. | A function is continuous on a set if it is continuous in every point of the set. | ||
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* The sum and product of two continuous functions are continuous functions. | * The sum and product of two continuous functions are continuous functions. | ||
* The composition of two continuous functions is a continuous function. | * The composition of two continuous functions is a continuous function. | ||
− | * In any closed interval <math>[a, b]</math>, there exist real numbers <math>c</math> and <math>d</math> such that <math>f</math> has a [[maximum]] value at <math>c</math> and <math>f</math> has a [[minimum]] value at <math>d</math>. | + | * In any closed interval <math>[a, b]</math>, there exist real numbers <math>c</math> and <math>d</math> such that <math>f</math> has a [[maximum]] value at <math>c</math> and <math>f</math> has a [[minimum]] value at <math>d</math>. |
− | * | + | * If a function is continuous, then it has the [[Intermediate Value Theorem]]. The converse is not always true. |
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− | If a function is continuous, then it has the [[Intermediate Value Theorem]]. The converse is not always true. | ||
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===Differentiability=== | ===Differentiability=== | ||
+ | Differentiability is a smoothness condition on functions. For functions of one variable, differentiability is simply the question of whether or not a [[derivative]] exists. For functions of more than one variable, the notion of differentiability is significantly more complicated. In the case of both one and multivariable functions, differentiability implies continuity. | ||
− | + | A single-variable function <math>f(x)</math> is differentiable at <math>x=a</math> if <math>\lim_{x\rightarrow a} \frac{f(x)-f(a)}{x-a} \in \mathbb{R}</math>. The derivative is the value of this [[limit]]. | |
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− | A single-variable function <math>f(x)</math> is differentiable at <math>x=a</math> | ||
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===Integrability=== | ===Integrability=== | ||
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All continuous functions are integrable, as well as many non-continuous functions. | All continuous functions are integrable, as well as many non-continuous functions. | ||
===Convexity=== | ===Convexity=== | ||
− | + | A twice-differentiable function <math>f(x) </math> is concave up (or ''convex'') in the interval <math>[a,b] </math> if <math>f''(x)>0</math> in the interval <math>[a,b] </math> and concave down (or ''concave'') if <math>f''(x)<0 </math>. The points of inflection, when the concavity switches, of the function occur at the roots of <math>f''(x) </math>. | |
− | A twice-differentiable function <math>f(x) </math> is concave up (or ''convex'') in the interval <math>[a,b] </math> | ||
==Notation== | ==Notation== | ||
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Find <math>f(84)</math>. | Find <math>f(84)</math>. | ||
([[1984 AIME Problems/Problem 7|Source]]) | ([[1984 AIME Problems/Problem 7|Source]]) | ||
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===Olympiad=== | ===Olympiad=== | ||
*Let <math>f</math> be a function with the following properties: | *Let <math>f</math> be a function with the following properties: | ||
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Prove that <math>f(n)=n</math>. | Prove that <math>f(n)=n</math>. | ||
([[1969 Canadian MO Problems/Problem 8|Source]]) | ([[1969 Canadian MO Problems/Problem 8|Source]]) | ||
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===Advanced=== | ===Advanced=== | ||
*Describe all polynomials <math>P(x)</math> such that <math>P(x + 1) - 1 = P(x) + P'(x)</math> for all <math>x</math>. | *Describe all polynomials <math>P(x)</math> such that <math>P(x + 1) - 1 = P(x) + P'(x)</math> for all <math>x</math>. | ||
− | (<url> | + | (<url>weblog_entry.php?t=182628 Source</url>) |
==See Also== | ==See Also== | ||
− | *[[Algebra]] | + | *[[Odd function]] |
− | **[[Functional equation]] | + | *[[Even function]] |
− | **[[Polynomials]] | + | * [[Algebra]] |
− | *[[Calculus]] | + | ** [[Functional equation]] |
− | **[[Limit]] | + | ** [[Polynomials]] |
− | **[[Derivative]] | + | * [[Calculus]] |
− | **[[Integral]] | + | ** [[Limit]] |
− | + | ** [[Derivative]] | |
+ | ** [[Integral]] | ||
[[Category:Algebra]] | [[Category:Algebra]] | ||
[[Category:Definition]] | [[Category:Definition]] | ||
[[Category:Functions]] | [[Category:Functions]] |
Latest revision as of 02:16, 12 May 2023
A function is a rule that maps one set of values to another set of values, assigning to each value in the first set exactly one value in the second. For instance, one function may map 1 to 1, 2 to 4, 3 to 9, 4 to 16, and so on. This function has the rule that it takes its input value, and squares it to get an output value. One can call this function .
Contents
Rigorous Definition
Let , be sets and let be a subset of , which denotes the Cartesian product of and . (That is, is a relation between and .) We say that is a function from to (written ) if and only if
- For every there is some such that , and
- if and then . (Here is an ordered pair.)
Introductory Topics
Domain and Range
The domain of a function is the set of input values for the argument of a function. The range of a function is the set of output values for that function. For an example, consider the function: . The domain of the function is the set , where is a real number, because the square root is only defined when its argument is nonnegative. The range is the set of all non-negative real numbers, because the square root can never return a negative value.
Real Functions
A real function is a function whose range is in the real numbers. Usually we speak about functions whose domain is also a subset of the real numbers.
Graphs
Functions are often graphed. A graph corresponds to a function only if it stands up to the vertical line test.
Inverses
The inverse of a function is a function that "undoes" a function. For an example, consider the function: . The function has the property that . Therefore, is called the (right) inverse function. (Similarly, a function that satisfies is called the left inverse function. Typically the right and left inverses coincide on a suitable domain, and in this case we simply call the right and left inverse function the inverse function.) Often the inverse of a function is denoted by .
Intermediate Topics
Injections, Surjections, Bijections
- An injection (or one-to-one function) is a function which always gives distinct values for distinct arguments within a given domain.
- By definition, is injective if , or equivalently,
- Injectivity of a function implies that has an inverse. Furthermore, if and are finite sets, injectivity implies .
- A surjection (or onto function) maps at least one element from its domain, onto every element of its range,
- A bijection (or one-to-one correspondence, which must be one-to-one and onto) is a function, that is both injective and surjective.
- If is an injection from and is an injection from then there exists a bijection, between and . This is the Schroeder-Bernstein Theorem.
Examples
- is injective and surjective (and therefore bijective) from .
- is injective from .
- is surjective from .
- is neither injective from (since ) nor surjective from (since does not map any value to , which is an element of ).
Monotonic functions
A function is called monotonically increasing if holds whenever . If the inequality holds strictly , then the function is called strictly increasing.
Similarly, a function is called monotonically decreasing if holds whenever . If the inequality holds strictly , then the function is called strictly decreasing.
Advanced Topics
Functions of Real Variables
A real function is a function whose range is in the real numbers. Usually we speak about function whose domain is also a subset of the real numbers.
Continuity
Intuitively, a continuous function has the propriety that its graph can be drawn without taking the pencil off the paper. To rigorously define continuous functions, more complex mathematics is necessary.
Epsilon-Delta Definition
A function is called continuous at some point in its domain if, for all , there exists such that, for any , the condition implies that .
Heine Definition
The previous definition of continuity at is equivalent with the following: for every sequence such that , we have that .
It is easy to see that a function is continuous in isolated points, and is continuous in large groups of points if the limit of the function in those points equals the value of the function.
A function is continuous on a set if it is continuous in every point of the set.
Properties of Continuous Functions
- The sum and product of two continuous functions are continuous functions.
- The composition of two continuous functions is a continuous function.
- In any closed interval , there exist real numbers and such that has a maximum value at and has a minimum value at .
- If a function is continuous, then it has the Intermediate Value Theorem. The converse is not always true.
Differentiability
Differentiability is a smoothness condition on functions. For functions of one variable, differentiability is simply the question of whether or not a derivative exists. For functions of more than one variable, the notion of differentiability is significantly more complicated. In the case of both one and multivariable functions, differentiability implies continuity.
A single-variable function is differentiable at if . The derivative is the value of this limit.
Integrability
All continuous functions are integrable, as well as many non-continuous functions.
Convexity
A twice-differentiable function is concave up (or convex) in the interval if in the interval and concave down (or concave) if . The points of inflection, when the concavity switches, of the function occur at the roots of .
Notation
A common notation to define is: (where the , of course, is merely an example). This tells us that is a function that squares its argument (its input value). Note that this "rule" can be arbitrarily complicated and doesn't need to be given by a simple formula or description. The only requirement is that should be uniquely determined by . The following are examples of functions:
- for , otherwise
History of Functions
Without being used explicitly, the notion of function first appears with the ancient Greeks and Egyptians.
The rigorous definition was stated in the 19th century and is the result of the works of some famous mathematicians: A.L. Cauchy, Leonhard Euler, and Bernhard Riemann. With the development of set theory, a new branch of mathematics appeared, mathematical analysis, in which the notion of function has a central role.
The current notation used is attributed to Leonhard Euler.
Problems
Introductory
- Define . What is ?
(Source)
Intermediate
Find . (Source)
Olympiad
- Let be a function with the following properties:
- is defined for every positive integer ;
- is an integer;
- ;
- for all and ;
- whenever .
Prove that . (Source)
Advanced
- Describe all polynomials such that for all .
(<url>weblog_entry.php?t=182628 Source</url>)