Authors

  • Boburjon Adilov
    Jizzakh Polytechnic Institute

DOI:

https://doi.org/10.71337/inlibrary.uz.jasss.71482

Abstract

Convexity, inflection points, and asymptotes of a function in this paper. The full function check is thought out and explained with examples.

 

 

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347

CONVEXITIES, INFLECTION POINTS, AND ASYMPTOTES OF THE FUNCTION.

FULL FUNCTION CHECK

Adilov Boburjon Bakhridin ugli

Jizzakh Polytechnic Institute

PhD, Associate Professor .

Abstract:

Convexity, inflection points, and asymptotes of a function in this paper. The full

function check is thought out and explained with examples.

Keywords:

function, skewness, point, derivative, graph.

Suppose that

�(�)

the function

(�, �)

is given by , and let be

1

, �

2

∈ (�, �)

for

1

< �

2

.

�(�)

a straight line passing through the points

� = �(�)

of the graph of a function

(�

1

, �(�

1

)), (�

2

, �(�

2

))

, it is as follows:

�(�) =

2

− �

2

− �

1

�(�

1

) +

� − �

1

2

− �

1

�(�

2

)

will be.
Definition

1. If

in

(�

1

, �

2

) ⊂ (�, �)

any interval settled​

∀� ∈ (�

1

, �

2

)

for

�(�) ≤ �(�)(�(�) < �(�))

If ,

�(�)

the function

(�, �)

is called a concave (strictly concave) function.

Definition 2.

If on

(�

1

, �

2

) ⊂ (�, �)

any island for settling

х ∈ (х

1

,

х

2

)

down

�(�) ≥ �(�) �(�) > �(�)

If ,

)

(

x

f

the function

)

,

(

b

a

is called a convex (strictly convex) function.

concave and convex functions are depicted in Figure 1 :


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Drawing 1.

Let's say,

1

≥ 0, �

2

≥ 0, �

1

+ �

1

= 1

be and

х

1

,

х

2

∈ (

а, �)

be. The concave and convexity of a

function can also be defined as follows.

Definition 3.

If

�(�

1.

1

+ �

2

2

) ≤ �

1

1

(�

1

) + �

2

�(�

2

)

�(�

1.

1

+ �

2

2

) < �

1

�(�

1

) + �

2

�(�

2

)

If ,

�(�)

the function

(�, �)

is said to be concave (strictly concave).

Definition 4.

If

�(�

1.

1

+ �

2

2

) ≥ �

1

1

(�

1

) + �

2

�(�

2

)

�(�

1.

1

+ �

2

2

) > �

1

�(�

1

) + �

2

�(�

2

)

If ,

�(�)

the function is said to

(�, �)

be convex (strictly convex) .

Example 1.

This

​ ​

�(�) = �

2

The function is

R

also a strictly concave function.

Solution

. Using Definition 3, we find:

�(�

1

1

+ �

2

2

) = (�

1

1

+ �

2

2

)

2

= (�

1

1

)

2

+ 2�

1

2

1

2

+ (�

2

2

)

2

<

< �

1

2

1

2

+ �

1

2

(�

1

+ �

2

)

2

+ �

2

2

2

2

= �

1

1

2

(�

1

+ �

2

) + �

2

2

2

(�

1

+ �

2

) =

= �

1

1

2

+ �

2

2

2

= �

1

�(�

1

) + �

2

�(�

2

)

Theorem 1.

Suppose that

�(�)

the function is

(�, �)

given at

and

has a derivative at .

�(�)

For the

function

'

(�)

to

(�, �)

be

concave at (strictly concave at ) ,

'

(�)

then the

function is

(�, �)

increasing at (strong growth) is necessary and is diverse .


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349

Necessity.

Let

�(�)

the function

(�, �)

be concave . In

∀�

1

, �

2

∈ (�, �),

that case

1

< �

2

, ∀� ∈

(�

1

, �

2

)

for

�(�) ≤

2

− �

2

− �

1

�(�

1

) +

� − �

1

2

− �

1

�(�

2

)

from which

�(�) − �(�

1

)

� − �

1

�(�

2

) − �(�)

2

− �

It turns out that (

2

− �

1

= (�

2

− �) + (� − �

1

)

it was said). In the next inequality,

� → �

1

after

� → �

2

passing to the limit,

'

(�

1

) ≤

�(�

2

) − �(�

1

)

2

− �

1

,

'

(�

2

) ≥

�(�

2

) − �(�

1

)

2

− �

1

We find that it will be. From it

'

(�

1

) ≤ �

'

(�

2

)

to be​

come​ ​

It turns out that

'

(�)

the

function is increasing on (a,b) .

�(�)

the function

(�, �)

be strictly concave. In that case

�(�) − �(�

1

)

� − �

1

<

�(�

2

) − �(�)

2

− �

According to Lagrange's theorem,

�(�) − �(�

1

)

� − �

1

= �

'

(�

1

), �

1

< �

1

< �;

�(�

2

) − �(�)

2

− �

= �

'

(�

2

), � < �

2

< �

2

It is, and it follows from it

)

(

)

(

2

1

x

f

x

f

<

that it is .

Sufficiency

. Let

'

(�)

the function

(�, �)

be increasing (strictly increasing):

∀�

1

, �

2

∈ (�, �),

2

1

x

x

<

at

'

(�

1

) ≤ �

'

(�

2

)

(

'

(�

1

) < �

'

(�

2

)

).

Using Lagrange 's theorem , we find :​


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350

�(�) − �(�

1

)

� − �

1

= �

'

(�

1

), �

1

< �

1

< �;

�(�

2

)−�(�)

2

−�

= �

'

2

, � < �

2

< �

2

.

Ravshanki ,.

1

< �

1

< � < �

2

< �

2

⇒ �

1

< �

2

D e mak ,

'

(�

1

) ≤ �

'

(�

2

)

(�

'

(�

1

) < �

'

(�

2

))

above​ ​ ​ ​ ​ ​ from these days

�(�)−�(�

1

)

�−�

1

�(�

2

)−�(�)

2

−�

�(�)−�(�

1

)

�−�

1

<

�(�

2

)−�(�)

2

−�

to be​ come​ ​ It comes out . This and

�(�)

function

(�, �)

at deep ( solid )​ ​ ​ that it is a

swamp indicates .
Huddy​ to that oh ʻх shash , the following theorem​ ​ ​ ​ also It is proven .

Theorem 2 .​ ​ ​ ​

�(�)

function

(�, �)

at given​ ​ to be , then​

'

(�)

to the end has Let

it be .

�(�)

function

(�, �)

at convex ( solid )​

convex​ ​ ​ ​

for

'

(�)

of

(�, �)

at decreasing

( constant )​ decreasing ( to be ) necessary and it is different .

Theorem 3 .​ ​ ​ ​

�(�)

function

(�, �)

in the interval to be concave ( convex )​ ​ ​

for

(�, �)

at

� ≥ 0 (�

(�) ≤ 0)

It is necessary and sufficient to be.
The proof of this theorem follows from the above theorem and the theorem on the monotonicity

of a function.

Example 2.

This

�(�) = �� � (� > 0)

the function is convex.

For this function

(�) =−

1

2

< 0

According to Theorem 2, the given

x

x

f

ln

)

(

=

function

(

)

+

,

0

is also strictly convex.

Inflection points of a function.

Suppose that

�(�)

the function

� ⊂ �

is given on a set, and

0

�, (�

0

− �, �

0

+ �) ⊂ �, � > 0

let .


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Definition 5.

If

�(�)

a function is

(�

0

− �, �

0

)

concave (convex) at

(�

0

, �

0

+ �)

and convex

(concave) at,

0

the point is called

�(�)

an inflection point

of the function .

Suppose

�(�)

the function

(�

0

− �, �

0

+ �)

has a derivative at .

(�)

If

х ∈ (х

0

− �,

х

0

)

at

(�) ≥ 0

)

0

)

(

(

x

f

,

х ∈ (х

0

,

х

0

+ �, )

at

(�) ≤ 0

)

0

)

(

(

x

f

,

If ,

'

(�)

the function

0

reaches an extremum at the point and therefore ,

(�

0

) = 0

becomes .

Therefore ,

�(�)

function bending at the point

(�) = 0

It will be .

Example 3 .​ ​

This

� � = �

3

function

0

= 0

on point bends .

This function for

(�) = 6

х

is,

х ∈ ( − �, 0)

at

(�) < 0

х ∈ (0, �, )

at

(�) > 0

)

0

(

>

d

will be.

Asymptotes of a function graph

Suppose that

�(�)

the function

� ⊂ �

is given on a set, and

0

the point

is a limit point of the set.

Definition 6.

If this

���

�→�

0

+0

�(�), ���

�→�

0

−0

�(�)

if one or both of the limits are infinite,

� = �

0

A straight line

�(�)

is called the vertical asymptote

of the graph of a function.

For example ,

�(�) =

1

х

function graph for

� = 0

right​ ​ ​ ​ line vertical​ ​ asymptote​ ​

It will be .
Let's say

�(�)

the function

(�

0

, + ∞)

is defined in .

Definition 7.

If such

and

such numbers are found,

�(�) = �� + � + �(�)(� →+ ∞ �� �(�) → 0)


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If , then

� = �� + �

the straight line

�(�)

is called the oblique asymptote of the graph of the

function.

Theorem 4.

so that

�(�)

the graph of the function

� = �� + �

has a g - axis asymptote

���

�→+∞

�(�)

� = �, ���

�→+∞

(�(�) − ��) = �

It is necessary and necessary .

Necessity.

� = �� + �

straight line

�(�)

function Let the graph of ω be an asymptote . Then

�(�) = �� + � + �(�)

is,

� →+ ∞да�(�) → 0

is. Taking this equality into account, we find:

���

�→+∞

�(�)

= ���

�→+∞

�� + � + ��

= �;

���

�→+∞

(�(�) − ��) = ���

�→+∞

(� + �(�)) = �.

Sufficiency

. This

���

�→+∞

�(�)

� = �, ���

�→+∞

(�(�) − ��) = �

relationships should be appropriate. From these relationships

(�(�) − ��) − � = �(�) → 0 ⇒ �(�) = �� + � + �(�)

It turns out to be.

Example 5 .

�(�) =

3

(�−1)

2

Find the oblique asymptote of the function.

For this function

� = ���

�→+∞

�(�)

= ���

�→+∞

2

(� − 1)

2

= 1;

� = ���

�→+∞

(�(�) − ��) = ���

�→+∞

3

(� − 1)

2

− � = 2

Thus,

� = � + 2

a straight line is a diagonal asymptote of the graph of a given function.


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353

Fully investigate and graph the function

� = �(�)

It is advisable to study the function in a certain sequence.

1. Find the domain of the function.
2. Find the points of intersection of the graph with the coordinate axes (if possible).
3. Find the intervals on which the sign of the function does not change (

�(�) > �

or

�(�) < �

).

4. Determine whether the function is even, odd, or neither even nor odd.
5. Find the asymptotes of the graph of the function.
6. Find the intervals of monotonicity of the function.
7. Find the extrema of the function.
8. Find the convex intervals and inflection points of the graph of the function.

Example 6.

This

� =

1

+ 4�

2

Examine the function and graph it.

Solution:

1) domain of definition of the function

� � : −∞; 0 ∪ 0; + ∞ ; � = 0

breakpoint of

a function;
2) We find the points of intersection of the function with the coordinate axes:

��

the axis

� = 0, � =−

3

2

2

,

��

the axis .

3)

−∞; −

3

2

2

∪ 0; + ∞ �� � > 0

,

3

2

2

; 0 �� � < 0;


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354

4)

� −� =−

1

+ 4�

2

≠ �(�) ≠ �( − �)

the function is neither even nor odd;

5) Vertical asymptote

� = 0.

We find the oblique asymptote.

� = �� + �

6)

lim

�→∞

1

+4�

2

= lim

�→∞

1

2

+ 4� = ∞

there is no obtuse asymptote;

7) We find the monotone intervals and extremum values of the function:

'

=

1

+ 4�

2

'

=−

1

2

+ 8� =

−1+8�

3

2

;

'

= 0 ⟹ − 1 + 8�

3

= 0 ⟹

� =

1
2

extremum point.

( − ∞; 0)

(0;

1
2 )

1
2

1
2 ; + ∞

���

= 3

�'

0

+

8) We find convex intervals and inflection points:

''

= −

1

2

+ 8�

'

=

2

3

+ 8 =

2(4�

3

+ 1)

3

; �

''

= 0

⟹ 4�

3

+ 1 = 0 ⟹ � =−

3

2

2

inflection point.

−∞; −

3

2

2

3

2

2

3

2

2

; 0

0; + ∞

� = 0

'

'

+

0

+

Let's graph the function using the above findings:


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References

1.

O ' . Toshmetov , R . M . Turg ' unboev , E . M . Saydamatov , M . Madirimov

“ Mathematical analysis ” ( part 1 ), (179-182 p ). Tashkent . 2015.
2.

Sh . A . Ayupov , M . A . Berdikulov , R . M . Turg ' unboev “ Functional analysis ”.

T .2007.
3.

Adilov B. B. Monotone sequences and the concept of their limits // Scientific information

of Bukhara State University. – 6/2024
4.

Adilov BB Convergences of sequences of dimensional functions // Scientific information

of Namangan State University. Issue 4, 2024.
5.

Bakhridinovich AB Theoretical bases of formation of design-design competence of future

engineers in the process of higher education. - 2022.
6.

Adilov B. ORGANIZATIONAL AND PEDAGOGICAL FOUNDATIONS OF THE

FORMATION OF PROJECT-DESIGN COMPETENCE OF STUDENTS OF THE

ENGINEERING DIRECTION //Science and innovation. - 2022. - T. 1. – no. B4. - S. ​ 318-322.

References

O ' . Toshmetov , R . M . Turg ' unboev , E . M . Saydamatov , M . Madirimov “ Mathematical analysis ” ( part 1 ), (179-182 p ). Tashkent . 2015.

Sh . A . Ayupov , M . A . Berdikulov , R . M . Turg ' unboev “ Functional analysis ”. T .2007.

Adilov B. B. Monotone sequences and the concept of their limits // Scientific information of Bukhara State University. – 6/2024

Adilov BB Convergences of sequences of dimensional functions // Scientific information of Namangan State University. Issue 4, 2024.

Bakhridinovich AB Theoretical bases of formation of design-design competence of future engineers in the process of higher education. - 2022.

Adilov B. ORGANIZATIONAL AND PEDAGOGICAL FOUNDATIONS OF THE FORMATION OF PROJECT-DESIGN COMPETENCE OF STUDENTS OF THE ENGINEERING DIRECTION //Science and innovation. - 2022. - T. 1. – no. B4. - S. ​318-322.