Computer Oriented Numerical Analysis
What is interpolation?
Many times, data is given only at discrete points such as .
So, how then does one find the value of y at any other value of x ?
Well, a continuous function f(x) may be used to represent the data values with f(x) passing through the points (Figure 1). Then one can find the value of y at any other value of x .
This is called interpolation
Newton’s Divided Difference Formula:
To illustrate this method, linear and quadratic interpolation is presented first.
Then, the general form of Newton’s divided difference polynomial method is presented.
Newton's Backward Interpolation explained with example. History of interpolation along with it's advantages and disadvantages. Applications of interpolation in computer sciences.
Gauss jordan and Guass elimination methodMeet Nayak
This ppt is based on engineering maths.
the topis is Gauss jordan and gauss elimination method.
This ppt having one example of both method and having algorithm.
Computer Oriented Numerical Analysis
What is interpolation?
Many times, data is given only at discrete points such as .
So, how then does one find the value of y at any other value of x ?
Well, a continuous function f(x) may be used to represent the data values with f(x) passing through the points (Figure 1). Then one can find the value of y at any other value of x .
This is called interpolation
Newton’s Divided Difference Formula:
To illustrate this method, linear and quadratic interpolation is presented first.
Then, the general form of Newton’s divided difference polynomial method is presented.
Newton's Backward Interpolation explained with example. History of interpolation along with it's advantages and disadvantages. Applications of interpolation in computer sciences.
Gauss jordan and Guass elimination methodMeet Nayak
This ppt is based on engineering maths.
the topis is Gauss jordan and gauss elimination method.
This ppt having one example of both method and having algorithm.
Integration Made Easy!
The derivative of a function can be geometrically interpreted as the slope of the curve of the mathematical function f(x) plotted as a function of x. But its implications for the modeling of nature go far deeper than this simple geometric application might imply. After all, you can see yourself drawing finite triangles to discover slope, so why is the derivative so important? Its importance lies in the fact that many physical entities such as velocity, acceleration, force and so on are defined as instantaneous rates of change of some other quantity. The derivative can give you a precise intantaneous value for that rate of change and lead to precise modeling of the desired quantity.
Here we focuses on Fixed-Point Iterative Technique for solving nonlinear Equations in Numerical Analysis. It is one of the opened-iterative techniques for finding roots called Fixed-Point of Non-linear Equations.
Integration Made Easy!
The derivative of a function can be geometrically interpreted as the slope of the curve of the mathematical function f(x) plotted as a function of x. But its implications for the modeling of nature go far deeper than this simple geometric application might imply. After all, you can see yourself drawing finite triangles to discover slope, so why is the derivative so important? Its importance lies in the fact that many physical entities such as velocity, acceleration, force and so on are defined as instantaneous rates of change of some other quantity. The derivative can give you a precise intantaneous value for that rate of change and lead to precise modeling of the desired quantity.
Here we focuses on Fixed-Point Iterative Technique for solving nonlinear Equations in Numerical Analysis. It is one of the opened-iterative techniques for finding roots called Fixed-Point of Non-linear Equations.
This learner's module discusses or talks about the topic of Quadratic Functions. It also discusses what is Quadratic Functions. It also shows how to transform or rewrite the equation f(x)=ax2 + bx + c to f(x)= a(x-h)2 + k. It will also show the different characteristics of Quadratic Functions.
First principle, power rule, derivative of constant term, product rule, quotient rule, chain rule, derivatives of trigonometric functions and their inverses, derivatives of exponential functions and natural logarithmic functions, implicit differentiation, parametric differentiation, L'Hopital's rule
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
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Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Forklift Classes Overview by Intella PartsIntella Parts
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4. What is Interpolation ?
Given (x0,y0), (x1,y1), …… (xn,yn), find the
value of ‘y’ at a value of ‘x’ that is not given.
5. Newton’s Divided Difference
Method
Linear interpolation: Given pass a
linear interpolant through the data
where
),,( 00 yx ),,( 11 yx
)()( 0101 xxbbxf −+=
)( 00 xfb =
01
01
1
)()(
xx
xfxf
b
−
−
=
6. Divided differences and the coefficients
f
ix [ ]if x
The divided difference of a function,
with respect to is denoted as
It is called as zeroth divided difference and is
simply the value of the function, f
at ix
[ ] ( )ii xfxf =
7. [ ]1i if x , x +
fThe divided difference of a function,
called as the first divided difference, is
denoted
ixwith respect to and 1ix +
[ ]
[ ] [ ]1
1
1
i i
i i
i i
f x f x
f x , x
x x
+
+
+
−
=
−
8. fThe divided difference of a function,
called as the second divided difference, is
denoted as
ixwith respect to and1ix +, 2ix +
[ ]1 2i i if x , x , x+ +
[ ]
[ ] [ ]1 2 1
1 2
2
i i i i
i i i
i i
f x , x f x , x
f x , x , x
x x
+ + +
+ +
+
−
=
−
9. [ ]
[ ] [ ]
1 2 3
1 2 3 1 2
3
i i i i
i i i i i i
i i
f x , x , x , x
f x , x , x f x , x , x
x x
+ + +
+ + + + +
+
−
=
−
The third divided difference with respect to
ix 1ix + 2ix + 3ix +
, and,
10. The coefficients of Newton’s interpolating
polynomial are:
[ ]00 xfa =
[ ]101 x,xfa =
[ ]2102 x,x,xfa =
[ ]32103 x,x,x,xfa =
[ ]432104 x,x,x,x,xfa = and so on.
12. Example
Find Newton’s interpolating polynomial to
approximate a function whose 5 data points
are given below.
( )f x
2.0 0.85467
2.3 0.75682
2.6 0.43126
2.9 0.22364
3.2 0.08567
x
14. The 5 coefficients of the Newton’s interpolating
polynomial are:
[ ]0 0 0 85467a f x .= =
[ ]1 0 1 0 32617a f x , x .= = −
[ ]2 0 1 2 1 26505a f x , x , x .= = −
[ ]3 0 1 2 3 2 13363a f x , x , x , x .= =
[ ]4 0 1 2 3 4 2 02642a f x , x , x , x , x .= = −
15. ( ) ( )
( ) ( )
( ) ( ) ( )
( ) ( ) ( ) ( )
0 1 0
2 0 1
3 0 1 2
4 0 1 2 3
P x a a x x
a x x x x
a x x x x x x
a x x x x x x x x
= + −
+ − −
+ − − −
+ − − − −
16. ( ) ( )
( ) ( )
( ) ( ) ( )
( ) ( ) ( ) ( )
0 85467 0 32617 2 0
-1.26505 2 0 2 3
2 13363 2 0 2 3 2 6
2 02642 2 0 2 3 2 6 2 9
P x . . x .
x . x .
. x . x . x .
. x . x . x . x .
= − −
− −
+ − − −
− − − − −
P(x) can now be used to estimate the value of the
function f(x) say at x = 2.8.