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CREATED BY :-
UTKARSH PATEL (170010114038)
SUBMITTED TO :- NBD SIR
Partial Derivative Equations
 The partial derivative of f(x,y) w.r.t. x at a point
 The partial derivative of f(x,y) w.r.t. y at a point
(1)h
yxfyhxf
x
f
f
h
x yx
),(),(
lim
0000
00
0
)( ,
−+
=





∂
∂
=
→
k
yxfkyxf
y
f
y k
yxf ),(),(
lim
000
00
0
0
)( ,
−+
=





∂
∂
=
→
)( 00, yx
)( 00, yx
xyyxyx ffff ,,,• If (x,y) and its partial derivative
are defined throughout an open region and containing
a point(a,b) and all the are continuous at point (a,b)
then (a,b) then (a,b)
• Which is also known as clairaut’s theorem.
xyf yxf
f
• Laplace equation in 2-D is 02
2
2
2
=
∂
∂
+
∂
∂
y
f
x
f
• Laplace equation in 3-D is 02
2
2
2
2
2
=
∂
∂
+
∂
∂
+
∂
∂
z
f
y
f
x
f
0
6,6
3
2
2
2
2
2
2
2
2
23
=
∂
∂
+
∂
∂
−=
∂
∂
=
∂
∂
−=
y
u
x
u
x
y
u
x
x
u
xyxu
xy
z
yx
z
∂∂
∂
=
∂∂
∂ 22
• If having continuous second order
partial derivatives then both are
equal.
• This also commutative property.
),( yxfu =
)(
...
x
x
yx
yy
z
SHL
yxz
+
∂
∂
=
∂
∂
+=
1−
= x
xy
( )1
. −
∂
∂
=





∂
∂
∂
∂ x
yx
xy
z
x
)log( 11
yyxy xx −−
+=
[ ]yxy
yx
z
SHL
x
log1
...
1
2
+=
∂∂
∂ −
…..(1)
Again
( )x
yx
xx
z
SHR
+
∂
∂
=
∂
∂
...
( )yy
yy
z
y
x
log1+
∂
∂
=





∂
∂
∂
∂
11
1
log
log
−−
−
+=
+=
xx
x
x
yyxy
y
y
yxy
[ ] )2.......(log1
...
1
2
yxy
xy
z
SHR
x
+=
∂∂
∂ −
Form (1) & (2) clairaut’s
Equation is clerified
 For two independent value of functions
 w= has continuous partial derivative
and if x=x(t) , y=y(t) are differentiable
function of t than the composite function
is a differentiable function of t and derivative is
),( yxf
yx f
y
f
f
x
f
=
∂
∂
=
∂
∂
,
))(),(( tytxfW =
t
y
y
w
t
x
x
w
dt
dw
∂
∂
∂
∂
+
∂
∂
∂
∂
=
tytx
xyyxu
cot,2sin
42
==
+=
Than find
dt
du
when 0,00 ==⇒= yxt
Now
t
y
y
u
t
x
x
u
dt
du
∂
∂
∂
∂
+
∂
∂
∂
∂
=
324
12,32 xyx
dy
du
yxy
dx
du
+=+=
t
dt
dx
t
dt
dx
sin,2cos2 −==
Than
So ( )( ) ( )( )txyxtyxy
dt
du
sin12cos232 324
−+++=
txytxtytxy
dt
du
sin12sin2cos62cos4 324
−−+=
6
)0sin()1)(0(12)0sin()0()0cos()1(6)0cos()1)(0(4
0
324
=
−−+=
=
dt
du
dt
du
tNow
 The equation of the form =c is known as an
implicit function.
 If x is a function of two variable & y is again
function of x. Therefore we may regard is a
composite function x.
 Therefore derivative of w.r.t. x is
),( yxf
f
f
0,
)1(0
≠−=
∂
∂
∂
∂
+
∂
∂
=
∂
∂
∂
∂
+
∂
∂
∂
∂
=
y
y
x
f
f
f
dx
dy
x
y
y
f
x
f
x
y
y
f
x
x
x
f
dx
df
xay
xxa
x
y
f
f
x
y
xayf
yaxf
xyayxyxf
xyayx
y
x
y
x
23
32
23
23
244
244
54
45
054
054
05),(
5
−
−
=
∂
∂
−=
∂
∂
=−=
=−=
=−+=
=+
 If is a function of two independent variable x &
y is said to be homogeneous function of degree n.
 If it satisfied where is constant.
 E.g.

 It is Homogeneous Function
),( yxf
),(),( yxfyxf n
λλλ = λ
)2(),(
2),(
)2()()(),(
2),(
2333
223333
233
233
yxyxyxf
yxyxyxf
yxyxyxf
yxyxyxfu
++=
++=
++=
++==
λλλ
λλλλλλ
λλλλλ
Calculas

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Calculas

  • 1. CREATED BY :- UTKARSH PATEL (170010114038) SUBMITTED TO :- NBD SIR
  • 3.  The partial derivative of f(x,y) w.r.t. x at a point  The partial derivative of f(x,y) w.r.t. y at a point (1)h yxfyhxf x f f h x yx ),(),( lim 0000 00 0 )( , −+ =      ∂ ∂ = → k yxfkyxf y f y k yxf ),(),( lim 000 00 0 0 )( , −+ =      ∂ ∂ = → )( 00, yx )( 00, yx
  • 4. xyyxyx ffff ,,,• If (x,y) and its partial derivative are defined throughout an open region and containing a point(a,b) and all the are continuous at point (a,b) then (a,b) then (a,b) • Which is also known as clairaut’s theorem. xyf yxf f
  • 5. • Laplace equation in 2-D is 02 2 2 2 = ∂ ∂ + ∂ ∂ y f x f • Laplace equation in 3-D is 02 2 2 2 2 2 = ∂ ∂ + ∂ ∂ + ∂ ∂ z f y f x f
  • 7. xy z yx z ∂∂ ∂ = ∂∂ ∂ 22 • If having continuous second order partial derivatives then both are equal. • This also commutative property. ),( yxfu =
  • 8. )( ... x x yx yy z SHL yxz + ∂ ∂ = ∂ ∂ += 1− = x xy ( )1 . − ∂ ∂ =      ∂ ∂ ∂ ∂ x yx xy z x )log( 11 yyxy xx −− += [ ]yxy yx z SHL x log1 ... 1 2 += ∂∂ ∂ − …..(1) Again ( )x yx xx z SHR + ∂ ∂ = ∂ ∂ ... ( )yy yy z y x log1+ ∂ ∂ =      ∂ ∂ ∂ ∂ 11 1 log log −− − += += xx x x yyxy y y yxy [ ] )2.......(log1 ... 1 2 yxy xy z SHR x += ∂∂ ∂ − Form (1) & (2) clairaut’s Equation is clerified
  • 9.  For two independent value of functions  w= has continuous partial derivative and if x=x(t) , y=y(t) are differentiable function of t than the composite function is a differentiable function of t and derivative is ),( yxf yx f y f f x f = ∂ ∂ = ∂ ∂ , ))(),(( tytxfW = t y y w t x x w dt dw ∂ ∂ ∂ ∂ + ∂ ∂ ∂ ∂ =
  • 10. tytx xyyxu cot,2sin 42 == += Than find dt du when 0,00 ==⇒= yxt Now t y y u t x x u dt du ∂ ∂ ∂ ∂ + ∂ ∂ ∂ ∂ = 324 12,32 xyx dy du yxy dx du +=+= t dt dx t dt dx sin,2cos2 −== Than So ( )( ) ( )( )txyxtyxy dt du sin12cos232 324 −+++= txytxtytxy dt du sin12sin2cos62cos4 324 −−+= 6 )0sin()1)(0(12)0sin()0()0cos()1(6)0cos()1)(0(4 0 324 = −−+= = dt du dt du tNow
  • 11.  The equation of the form =c is known as an implicit function.  If x is a function of two variable & y is again function of x. Therefore we may regard is a composite function x.  Therefore derivative of w.r.t. x is ),( yxf f f 0, )1(0 ≠−= ∂ ∂ ∂ ∂ + ∂ ∂ = ∂ ∂ ∂ ∂ + ∂ ∂ ∂ ∂ = y y x f f f dx dy x y y f x f x y y f x x x f dx df
  • 13.  If is a function of two independent variable x & y is said to be homogeneous function of degree n.  If it satisfied where is constant.  E.g.   It is Homogeneous Function ),( yxf ),(),( yxfyxf n λλλ = λ )2(),( 2),( )2()()(),( 2),( 2333 223333 233 233 yxyxyxf yxyxyxf yxyxyxf yxyxyxfu ++= ++= ++= ++== λλλ λλλλλλ λλλλλ

Editor's Notes

  1. Outline: Central Scientific Problem – Artificial Intelligence Machine Learning: Definition Specifics Requirements Existing Solutions and their limitations Multiresolution Approximation: Limitation Our Approach. Results. Binarization. Plans.
  2. Outline: Central Scientific Problem – Artificial Intelligence Machine Learning: Definition Specifics Requirements Existing Solutions and their limitations Multiresolution Approximation: Limitation Our Approach. Results. Binarization. Plans.
  3. Outline: Central Scientific Problem – Artificial Intelligence Machine Learning: Definition Specifics Requirements Existing Solutions and their limitations Multiresolution Approximation: Limitation Our Approach. Results. Binarization. Plans.
  4. Outline: Central Scientific Problem – Artificial Intelligence Machine Learning: Definition Specifics Requirements Existing Solutions and their limitations Multiresolution Approximation: Limitation Our Approach. Results. Binarization. Plans.