Home > Numerical methods calculators > Numerical Differentiation using Newton's Backward Difference formula example

3. Newton's Backward Difference formula (Numerical Differentiation) example ( Enter your problem )
  1. Formula & Example-1 (table data)
  2. Example-2 (table data)
  3. Example-3 (`f(x)=2x^3-4x+1`)
  4. Example-4 (`f(x)=x^3+x+2`)
Other related methods
  1. Newton's Forward Difference formula
  2. Newton's Backward Difference formula
  3. Newton's Divided Difference formula
  4. Lagrange's formula
  5. Stirling's formula
  6. Bessel's formula

1. Formula & Example-1 (table data)
(Previous example)
3. Example-3 (`f(x)=2x^3-4x+1`)
(Next example)

2. Example-2 (table data)





Using Newton's Backward Difference formula to find solution
xf(x)
0.01.0000
0.10.9975
0.20.9900
0.30.9776
0.40.8604

x = 0.3


Solution:
Numerical differentiation method to find solution.
The value of table for `x` and `y`

x00.10.20.30.4
y10.99750.990.97760.8604

Newton's backward differentiation table is
xy`grady``grad^2y``grad^3y``grad^4y`
01
-0.0025
0.10.9975-0.005
-0.00750.0001
0.20.99-0.0049-0.1
-0.0124-0.0999
0.30.9776-0.1048
-0.1172
0.40.8604


The value of x at you want to find `f(x) : x_n = 0.3`

`h = x_1 - x_0 = 0.1 - 0 = 0.1`


`[(dy)/(dx)]_(x=x_n) = 1/h * (grad y_n + 1/2 * grad^2 y_n + 1/3 * grad^3 y_n + 1/4 * grad^4 y_n)`

`:.[(dy)/(dx)]_(x=0.3) = 1/0.1 xx (-0.0124 + 1/2 xx -0.0049 + 1/3 xx 0.0001 + 1/4 xx 0)`

`:.[(dy)/(dx)]_(x=0.3) = -0.1482`


`[(d^2y)/(dx^2)]_(x=x_n) = 1/h^2 * (grad^2 y_n + grad^3 y_n + 11/12 * grad^4 y_n)`

`:.[(d^2y)/(dx^2)]_(x=0.3) = 1/0.01 * (-0.0049 + 0.0001 + 11/12 xx 0)`

`:.[(d^2y)/(dx^2)]_(x=0.3) = -0.48`


`:.` `Pn'(0.3) = -0.1482` and `Pn''(0.3) = -0.48`


This material is intended as a summary. Use your textbook for detail explanation.
Any bug, improvement, feedback then Submit Here



1. Formula & Example-1 (table data)
(Previous example)
3. Example-3 (`f(x)=2x^3-4x+1`)
(Next example)





Share this solution or page with your friends.


 
Copyright © 2024. All rights reserved. Terms, Privacy
 
 

.