SlideShare a Scribd company logo
1 of 8
Download to read offline
MATHEMATICAL METHODS




NUMERICAL DIFFERENTIATION & INTEGRATION

                            I YEAR B.Tech
                    AS PER JNTU-HYDERABAD NEW SYLLABUS




By
Mr. Y. Prabhaker Reddy
Asst. Professor of Mathematics
Guru Nanak Engineering College
Ibrahimpatnam, Hyderabad.
SYLLABUS OF MATHEMATICAL METHODS (as per JNTU Hyderabad)

Name of the Unit                                      Name of the Topic
                     Matrices and Linear system of equations: Elementary row transformations – Rank
      Unit-I
                     – Echelon form, Normal form       – Solution of Linear Systems    – Direct Methods        – LU
Solution of Linear
                     Decomposition from Gauss Elimination – Solution of Tridiagonal systems – Solution
    systems
                     of Linear Systems.
                     Eigen values, Eigen vectors     – properties   – Condition number of Matrix, Cayley               –
     Unit-II
                     Hamilton Theorem (without proof)       – Inverse and powers of a matrix by Cayley             –
Eigen values and
                     Hamilton theorem       – Diagonalization of matrix Calculation of powers of matrix
                                                                         –                                     –
  Eigen vectors
                     Model and spectral matrices.
                     Real Matrices, Symmetric, skew symmetric, Orthogonal, Linear Transformation -
                     Orthogonal Transformation. Complex Matrices, Hermition and skew Hermition
     Unit-III
                     matrices, Unitary Matrices - Eigen values and Eigen vectors of complex matrices and
     Linear
                     their properties. Quadratic forms - Reduction of quadratic form to canonical form,
Transformations
                     Rank, Positive, negative and semi definite, Index, signature, Sylvester law, Singular
                     value decomposition.
                     Solution of Algebraic and Transcendental Equations- Introduction: The Bisection
                     Method – The Method of False Position       – The Iteration Method - Newton
                                                                                               –Raphson
                     Method Interpolation:Introduction-Errors in Polynomial Interpolation - Finite
     Unit-IV
                     differences- Forward difference, Backward differences, Central differences, Symbolic
Solution of Non-
                     relations and separation of symbols-Difference equations           – Differences of a
 linear Systems
                     polynomial - Newton’s Formulae for interpolation - Central difference interpolation
                     formulae - Gauss Central Difference Formulae - Lagrange’s Interpolation formulae- B.
                     Spline interpolation, Cubic spline.
     Unit-V          Curve Fitting: Fitting a straight line - Second degree curve - Exponential curve -
 Curve fitting &     Power curve by method of least squares.
   Numerical         Numerical Integration: Numerical Differentiation-Simpson’s         3/8    Rule,      Gaussian
   Integration       Integration, Evaluation of Principal value integrals, Generalized Quadrature.
     Unit-VI         Solution   by   Taylor’s s - Picard’s
                                              serie              Method   of   successive     approximation
                                                                                                   - Euler’s
   Numerical         Method -Runge kutta Methods, Predictor Corrector Methods, Adams- Bashforth
 solution of ODE     Method.
                     Determination of Fourier coefficients - Fourier series-even and odd functions -
    Unit-VII
                     Fourier series in an arbitrary interval - Even and odd periodic continuation - Half-
 Fourier Series
                     range Fourier sine and cosine expansions.
    Unit-VIII        Introduction and formation of PDE by elimination of arbitrary constants and
     Partial         arbitrary functions - Solutions of first order linear equation - Non linear equations -
   Differential      Method of separation of variables for second order equations - Two dimensional
   Equations         wave equation.
CONTENTS
UNIT-V
NUMERICAL DIFFERENTIATION & INTEGRATION
          Numerical Differentiation

          Numerical Integration

          Trapezoidal Rule

          Simpson’s 1/3 Rule

            Simpson’s 3/8 Rule
Numerical Differentiation and Integration
Numerical Differentiation
                                                                             Equally Spaced Arguments



Aim: We want to calculate                         at the tabulated points.

The intention of Using these formulas is that, without finding the polynomial for the given curve,
we will find its first, second, third, . . . derivatives.
Since Arguments are equally spaced, we can use Forward, Backward or Central differences.

                           Differentiation using Forward Differences
We know that
By Taylor’s Series expansion, we have



Define
so that              ,




Now,




Taking Log on both sides, we get




To find Second Derivative
We have
Squaring on both sides, we get




                                          (                        )




To find Third Derivative
We have

Cubing on both sides, we get




                      Differentiation using Backward differences
We know that
By Taylor’s Series expansion, we have



Define
so that           ,




Now,
Taking Log on both sides, we get




To find Second Derivative
We have

Squaring on both sides, we get




                                                  (                )




To find Third Derivative

We have

Cubing on both sides, we get




                       Differentiation using Central differences
We know that the Stirling’s Formula is given by
Where

Now, Differentiating w.r.t. , we get




At




Similarly,




When we have to use these formulae?
When we are asked to find         at the point         , the problem analyzing should be as follows:

If the point            is nearer to the starting arguments of the given table, then use Forward
difference formulas for differentiation
If the point            is nearer to the ending arguments of the given table, then use Backward
difference formulas for differentiation
If the point            is nearer to the Middle arguments of the given table, then use Central
difference formulas for differentiation.
Numerical Integration

We know that a definite integral of the form                   represents the area under the curve
             , enclosed between the limits       and         .

Let                  . Here the value of is a Numerical value.
Aim: To find the approximation to the Numerical value of . The process of finding the
approximation to the definite Integral is known as Numerical Integration.
Let                    be given set of observations, and let                  be the corresponding
values for the curve             .




This formulae is also known as Newton Cotes closed type Formulae.
        If        , the formula is known as Trapezoidal Rule
        If        , the formula is known as Simpson’s            Rule
If     , the formula is known as Simpson’s       Rule


Trapezoidal Rule



i.e.

Here   is number of Intervals, and

Simpson’s          Rule



i.e.


Simpson’s         Rule



i.e.
                                       2(                   ℎℎ                   3)

       If Even number of Intervals are there, it is preferred to use Simpson’s    Rule (Or)
       Trapezoidal Rule.
       If Number of Intervals is multiple of 3, then use Simpson’s     Rule (Or) Trapezoidal
       Rule.
       If Odd number of Intervals are there, and which is not multiple of 3, then use Trapezoidal
       Rule. Ex: 5, 7 etc.
       For any number of Intervals, the default Rule we can use is Trapezoidal.

More Related Content

What's hot

Linear differential equation
Linear differential equationLinear differential equation
Linear differential equationPratik Sudra
 
Numerical differentiation
Numerical differentiationNumerical differentiation
Numerical differentiationandrushow
 
Euler and improved euler method
Euler and improved euler methodEuler and improved euler method
Euler and improved euler methodSohaib Butt
 
Differential equations
Differential equationsDifferential equations
Differential equationsSeyid Kadher
 
linear equation and gaussian elimination
linear equation and gaussian eliminationlinear equation and gaussian elimination
linear equation and gaussian eliminationAju Thadikulangara
 
trapezoidal and simpson's 1/3 and 3/8 rule
trapezoidal and simpson's 1/3 and 3/8 ruletrapezoidal and simpson's 1/3 and 3/8 rule
trapezoidal and simpson's 1/3 and 3/8 rulehitarth shah
 
Application of vector integration
Application of vector integration Application of vector integration
Application of vector integration Varuna Kapuge
 
Coordinate transformation
Coordinate transformationCoordinate transformation
Coordinate transformationMohd Arif
 
Newton's Forward/Backward Difference Interpolation
Newton's Forward/Backward  Difference InterpolationNewton's Forward/Backward  Difference Interpolation
Newton's Forward/Backward Difference InterpolationVARUN KUMAR
 
Second order homogeneous linear differential equations
Second order homogeneous linear differential equations Second order homogeneous linear differential equations
Second order homogeneous linear differential equations Viraj Patel
 
application of differential equations
application of differential equationsapplication of differential equations
application of differential equationsVenkata.Manish Reddy
 
interpolation
interpolationinterpolation
interpolation8laddu8
 
application of first order ordinary Differential equations
application of first order ordinary Differential equationsapplication of first order ordinary Differential equations
application of first order ordinary Differential equationsEmdadul Haque Milon
 
First order linear differential equation
First order linear differential equationFirst order linear differential equation
First order linear differential equationNofal Umair
 
Partial Differential Equations, 3 simple examples
Partial Differential Equations, 3 simple examplesPartial Differential Equations, 3 simple examples
Partial Differential Equations, 3 simple examplesEnrique Valderrama
 
Numerical integration
Numerical integrationNumerical integration
Numerical integrationSunny Chauhan
 
Partial differential equations
Partial differential equationsPartial differential equations
Partial differential equationsaman1894
 

What's hot (20)

Linear differential equation
Linear differential equationLinear differential equation
Linear differential equation
 
Interpolation
InterpolationInterpolation
Interpolation
 
Numerical differentiation
Numerical differentiationNumerical differentiation
Numerical differentiation
 
Double Integrals
Double IntegralsDouble Integrals
Double Integrals
 
Euler and improved euler method
Euler and improved euler methodEuler and improved euler method
Euler and improved euler method
 
Differential equations
Differential equationsDifferential equations
Differential equations
 
linear equation and gaussian elimination
linear equation and gaussian eliminationlinear equation and gaussian elimination
linear equation and gaussian elimination
 
trapezoidal and simpson's 1/3 and 3/8 rule
trapezoidal and simpson's 1/3 and 3/8 ruletrapezoidal and simpson's 1/3 and 3/8 rule
trapezoidal and simpson's 1/3 and 3/8 rule
 
Application of vector integration
Application of vector integration Application of vector integration
Application of vector integration
 
Coordinate transformation
Coordinate transformationCoordinate transformation
Coordinate transformation
 
Newton's Forward/Backward Difference Interpolation
Newton's Forward/Backward  Difference InterpolationNewton's Forward/Backward  Difference Interpolation
Newton's Forward/Backward Difference Interpolation
 
Second order homogeneous linear differential equations
Second order homogeneous linear differential equations Second order homogeneous linear differential equations
Second order homogeneous linear differential equations
 
application of differential equations
application of differential equationsapplication of differential equations
application of differential equations
 
interpolation
interpolationinterpolation
interpolation
 
Analytic function
Analytic functionAnalytic function
Analytic function
 
application of first order ordinary Differential equations
application of first order ordinary Differential equationsapplication of first order ordinary Differential equations
application of first order ordinary Differential equations
 
First order linear differential equation
First order linear differential equationFirst order linear differential equation
First order linear differential equation
 
Partial Differential Equations, 3 simple examples
Partial Differential Equations, 3 simple examplesPartial Differential Equations, 3 simple examples
Partial Differential Equations, 3 simple examples
 
Numerical integration
Numerical integrationNumerical integration
Numerical integration
 
Partial differential equations
Partial differential equationsPartial differential equations
Partial differential equations
 

Viewers also liked

Core 3 Simpsons Rule
Core 3 Simpsons RuleCore 3 Simpsons Rule
Core 3 Simpsons Ruledavidmiles100
 
MILNE'S PREDICTOR CORRECTOR METHOD
MILNE'S PREDICTOR CORRECTOR METHODMILNE'S PREDICTOR CORRECTOR METHOD
MILNE'S PREDICTOR CORRECTOR METHODKavin Raval
 
Presentation on Numerical Method (Trapezoidal Method)
Presentation on Numerical Method (Trapezoidal Method)Presentation on Numerical Method (Trapezoidal Method)
Presentation on Numerical Method (Trapezoidal Method)Syed Ahmed Zaki
 
fourier series
fourier seriesfourier series
fourier series8laddu8
 
Numerical integration
Numerical integrationNumerical integration
Numerical integrationMohammed_AQ
 
Introduction to Numerical Analysis
Introduction to Numerical AnalysisIntroduction to Numerical Analysis
Introduction to Numerical AnalysisMohammad Tawfik
 
Numerical Methods - Oridnary Differential Equations - 1
Numerical Methods - Oridnary Differential Equations - 1Numerical Methods - Oridnary Differential Equations - 1
Numerical Methods - Oridnary Differential Equations - 1Dr. Nirav Vyas
 
Applied numerical methods lec11
Applied numerical methods lec11Applied numerical methods lec11
Applied numerical methods lec11Yasser Ahmed
 
09 numerical differentiation
09 numerical differentiation09 numerical differentiation
09 numerical differentiationMohammad Tawfik
 
Euler Method using MATLAB
Euler Method using MATLABEuler Method using MATLAB
Euler Method using MATLABM.Ahmed Waqas
 
2 Capitulo Metodos Numericos
2 Capitulo Metodos Numericos2 Capitulo Metodos Numericos
2 Capitulo Metodos NumericosDUBAN CASTRO
 
Matlab code for comparing two microphone files
Matlab code for comparing two microphone filesMatlab code for comparing two microphone files
Matlab code for comparing two microphone filesMinh Anh Nguyen
 
Matlab implementation of fast fourier transform
Matlab implementation of  fast fourier transformMatlab implementation of  fast fourier transform
Matlab implementation of fast fourier transformRakesh kumar jha
 

Viewers also liked (20)

Core 3 Simpsons Rule
Core 3 Simpsons RuleCore 3 Simpsons Rule
Core 3 Simpsons Rule
 
Numerical Methods 3
Numerical Methods 3Numerical Methods 3
Numerical Methods 3
 
21 simpson's rule
21 simpson's rule21 simpson's rule
21 simpson's rule
 
Unit vi
Unit viUnit vi
Unit vi
 
MILNE'S PREDICTOR CORRECTOR METHOD
MILNE'S PREDICTOR CORRECTOR METHODMILNE'S PREDICTOR CORRECTOR METHOD
MILNE'S PREDICTOR CORRECTOR METHOD
 
Presentation on Numerical Method (Trapezoidal Method)
Presentation on Numerical Method (Trapezoidal Method)Presentation on Numerical Method (Trapezoidal Method)
Presentation on Numerical Method (Trapezoidal Method)
 
fourier series
fourier seriesfourier series
fourier series
 
Numerical Integration
Numerical IntegrationNumerical Integration
Numerical Integration
 
Numerical integration
Numerical integrationNumerical integration
Numerical integration
 
Fourier series
Fourier seriesFourier series
Fourier series
 
Introduction to Numerical Analysis
Introduction to Numerical AnalysisIntroduction to Numerical Analysis
Introduction to Numerical Analysis
 
Numerical Methods - Oridnary Differential Equations - 1
Numerical Methods - Oridnary Differential Equations - 1Numerical Methods - Oridnary Differential Equations - 1
Numerical Methods - Oridnary Differential Equations - 1
 
Applied numerical methods lec11
Applied numerical methods lec11Applied numerical methods lec11
Applied numerical methods lec11
 
09 numerical differentiation
09 numerical differentiation09 numerical differentiation
09 numerical differentiation
 
Matiasy Kevin1
Matiasy Kevin1Matiasy Kevin1
Matiasy Kevin1
 
Nsm ppt.ppt
Nsm ppt.pptNsm ppt.ppt
Nsm ppt.ppt
 
Euler Method using MATLAB
Euler Method using MATLABEuler Method using MATLAB
Euler Method using MATLAB
 
2 Capitulo Metodos Numericos
2 Capitulo Metodos Numericos2 Capitulo Metodos Numericos
2 Capitulo Metodos Numericos
 
Matlab code for comparing two microphone files
Matlab code for comparing two microphone filesMatlab code for comparing two microphone files
Matlab code for comparing two microphone files
 
Matlab implementation of fast fourier transform
Matlab implementation of  fast fourier transformMatlab implementation of  fast fourier transform
Matlab implementation of fast fourier transform
 

Similar to numerical differentiation&integration

algebraic&transdential equations
algebraic&transdential equationsalgebraic&transdential equations
algebraic&transdential equations8laddu8
 
linear transformation
linear transformationlinear transformation
linear transformation8laddu8
 
partial diffrentialequations
partial diffrentialequationspartial diffrentialequations
partial diffrentialequations8laddu8
 
eigen valuesandeigenvectors
eigen valuesandeigenvectorseigen valuesandeigenvectors
eigen valuesandeigenvectors8laddu8
 
real andcomplexmatricesquadraticforms
real andcomplexmatricesquadraticformsreal andcomplexmatricesquadraticforms
real andcomplexmatricesquadraticforms8laddu8
 
Unit 1-solution oflinearsystems
Unit 1-solution oflinearsystemsUnit 1-solution oflinearsystems
Unit 1-solution oflinearsystems8laddu8
 
Day 9 combining like terms
Day 9 combining like termsDay 9 combining like terms
Day 9 combining like termsErik Tjersland
 
Motion graphs summary
Motion graphs summaryMotion graphs summary
Motion graphs summaryPatrick Cole
 
Modelling and Managing Ambiguous Context in Intelligent Environments
Modelling and Managing Ambiguous Context in Intelligent EnvironmentsModelling and Managing Ambiguous Context in Intelligent Environments
Modelling and Managing Ambiguous Context in Intelligent EnvironmentsAitor Almeida
 
Analyzing Statistical Results
Analyzing Statistical ResultsAnalyzing Statistical Results
Analyzing Statistical Resultsoehokie82
 
Methods1 relations and functions
Methods1 relations and functionsMethods1 relations and functions
Methods1 relations and functionskmcmullen
 
Methods1 relations and functions
Methods1  relations and functionsMethods1  relations and functions
Methods1 relations and functionskmcmullen
 
Oracle Crystal Ball Screens
Oracle Crystal Ball ScreensOracle Crystal Ball Screens
Oracle Crystal Ball ScreensDave Maskell
 
Methods2 polynomial functions
Methods2 polynomial functionsMethods2 polynomial functions
Methods2 polynomial functionskmcmullen
 

Similar to numerical differentiation&integration (20)

algebraic&transdential equations
algebraic&transdential equationsalgebraic&transdential equations
algebraic&transdential equations
 
linear transformation
linear transformationlinear transformation
linear transformation
 
partial diffrentialequations
partial diffrentialequationspartial diffrentialequations
partial diffrentialequations
 
eigen valuesandeigenvectors
eigen valuesandeigenvectorseigen valuesandeigenvectors
eigen valuesandeigenvectors
 
real andcomplexmatricesquadraticforms
real andcomplexmatricesquadraticformsreal andcomplexmatricesquadraticforms
real andcomplexmatricesquadraticforms
 
Unit 1-solution oflinearsystems
Unit 1-solution oflinearsystemsUnit 1-solution oflinearsystems
Unit 1-solution oflinearsystems
 
Day 9 combining like terms
Day 9 combining like termsDay 9 combining like terms
Day 9 combining like terms
 
Motion graphs summary
Motion graphs summaryMotion graphs summary
Motion graphs summary
 
Modelling and Managing Ambiguous Context in Intelligent Environments
Modelling and Managing Ambiguous Context in Intelligent EnvironmentsModelling and Managing Ambiguous Context in Intelligent Environments
Modelling and Managing Ambiguous Context in Intelligent Environments
 
Analyzing Statistical Results
Analyzing Statistical ResultsAnalyzing Statistical Results
Analyzing Statistical Results
 
Methods1 relations and functions
Methods1 relations and functionsMethods1 relations and functions
Methods1 relations and functions
 
Struds overview
Struds overviewStruds overview
Struds overview
 
G. Pillsbury Stanislaus Online Readiness at Stanislaus
G. Pillsbury Stanislaus Online Readiness at StanislausG. Pillsbury Stanislaus Online Readiness at Stanislaus
G. Pillsbury Stanislaus Online Readiness at Stanislaus
 
Methods1 relations and functions
Methods1  relations and functionsMethods1  relations and functions
Methods1 relations and functions
 
Rubik’s cube
Rubik’s cubeRubik’s cube
Rubik’s cube
 
Oracle Crystal Ball Screens
Oracle Crystal Ball ScreensOracle Crystal Ball Screens
Oracle Crystal Ball Screens
 
Simbol matematika dasar
Simbol matematika dasarSimbol matematika dasar
Simbol matematika dasar
 
ตัวจริง
ตัวจริงตัวจริง
ตัวจริง
 
Methods2 polynomial functions
Methods2 polynomial functionsMethods2 polynomial functions
Methods2 polynomial functions
 
Dr. Lesa Clarkson - University of Minnesota
Dr. Lesa Clarkson - University of MinnesotaDr. Lesa Clarkson - University of Minnesota
Dr. Lesa Clarkson - University of Minnesota
 

Recently uploaded

Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 
Transaction Management in Database Management System
Transaction Management in Database Management SystemTransaction Management in Database Management System
Transaction Management in Database Management SystemChristalin Nelson
 
Choosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for ParentsChoosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for Parentsnavabharathschool99
 
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...Postal Advocate Inc.
 
Barangay Council for the Protection of Children (BCPC) Orientation.pptx
Barangay Council for the Protection of Children (BCPC) Orientation.pptxBarangay Council for the Protection of Children (BCPC) Orientation.pptx
Barangay Council for the Protection of Children (BCPC) Orientation.pptxCarlos105
 
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxiammrhaywood
 
Culture Uniformity or Diversity IN SOCIOLOGY.pptx
Culture Uniformity or Diversity IN SOCIOLOGY.pptxCulture Uniformity or Diversity IN SOCIOLOGY.pptx
Culture Uniformity or Diversity IN SOCIOLOGY.pptxPoojaSen20
 
Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Jisc
 
Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Seán Kennedy
 
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONTHEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONHumphrey A Beña
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfTechSoup
 
Earth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatEarth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatYousafMalik24
 
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Celine George
 
ACC 2024 Chronicles. Cardiology. Exam.pdf
ACC 2024 Chronicles. Cardiology. Exam.pdfACC 2024 Chronicles. Cardiology. Exam.pdf
ACC 2024 Chronicles. Cardiology. Exam.pdfSpandanaRallapalli
 
Judging the Relevance and worth of ideas part 2.pptx
Judging the Relevance  and worth of ideas part 2.pptxJudging the Relevance  and worth of ideas part 2.pptx
Judging the Relevance and worth of ideas part 2.pptxSherlyMaeNeri
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designMIPLM
 
Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Mark Reed
 

Recently uploaded (20)

Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 
Transaction Management in Database Management System
Transaction Management in Database Management SystemTransaction Management in Database Management System
Transaction Management in Database Management System
 
Choosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for ParentsChoosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for Parents
 
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
 
Barangay Council for the Protection of Children (BCPC) Orientation.pptx
Barangay Council for the Protection of Children (BCPC) Orientation.pptxBarangay Council for the Protection of Children (BCPC) Orientation.pptx
Barangay Council for the Protection of Children (BCPC) Orientation.pptx
 
Raw materials used in Herbal Cosmetics.pptx
Raw materials used in Herbal Cosmetics.pptxRaw materials used in Herbal Cosmetics.pptx
Raw materials used in Herbal Cosmetics.pptx
 
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptxYOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
 
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
 
Culture Uniformity or Diversity IN SOCIOLOGY.pptx
Culture Uniformity or Diversity IN SOCIOLOGY.pptxCulture Uniformity or Diversity IN SOCIOLOGY.pptx
Culture Uniformity or Diversity IN SOCIOLOGY.pptx
 
Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...
 
Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...
 
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
 
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONTHEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
 
Earth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatEarth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice great
 
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
Incoming and Outgoing Shipments in 3 STEPS Using Odoo 17
 
ACC 2024 Chronicles. Cardiology. Exam.pdf
ACC 2024 Chronicles. Cardiology. Exam.pdfACC 2024 Chronicles. Cardiology. Exam.pdf
ACC 2024 Chronicles. Cardiology. Exam.pdf
 
Judging the Relevance and worth of ideas part 2.pptx
Judging the Relevance  and worth of ideas part 2.pptxJudging the Relevance  and worth of ideas part 2.pptx
Judging the Relevance and worth of ideas part 2.pptx
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-design
 
Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)
 

numerical differentiation&integration

  • 1. MATHEMATICAL METHODS NUMERICAL DIFFERENTIATION & INTEGRATION I YEAR B.Tech AS PER JNTU-HYDERABAD NEW SYLLABUS By Mr. Y. Prabhaker Reddy Asst. Professor of Mathematics Guru Nanak Engineering College Ibrahimpatnam, Hyderabad.
  • 2. SYLLABUS OF MATHEMATICAL METHODS (as per JNTU Hyderabad) Name of the Unit Name of the Topic Matrices and Linear system of equations: Elementary row transformations – Rank Unit-I – Echelon form, Normal form – Solution of Linear Systems – Direct Methods – LU Solution of Linear Decomposition from Gauss Elimination – Solution of Tridiagonal systems – Solution systems of Linear Systems. Eigen values, Eigen vectors – properties – Condition number of Matrix, Cayley – Unit-II Hamilton Theorem (without proof) – Inverse and powers of a matrix by Cayley – Eigen values and Hamilton theorem – Diagonalization of matrix Calculation of powers of matrix – – Eigen vectors Model and spectral matrices. Real Matrices, Symmetric, skew symmetric, Orthogonal, Linear Transformation - Orthogonal Transformation. Complex Matrices, Hermition and skew Hermition Unit-III matrices, Unitary Matrices - Eigen values and Eigen vectors of complex matrices and Linear their properties. Quadratic forms - Reduction of quadratic form to canonical form, Transformations Rank, Positive, negative and semi definite, Index, signature, Sylvester law, Singular value decomposition. Solution of Algebraic and Transcendental Equations- Introduction: The Bisection Method – The Method of False Position – The Iteration Method - Newton –Raphson Method Interpolation:Introduction-Errors in Polynomial Interpolation - Finite Unit-IV differences- Forward difference, Backward differences, Central differences, Symbolic Solution of Non- relations and separation of symbols-Difference equations – Differences of a linear Systems polynomial - Newton’s Formulae for interpolation - Central difference interpolation formulae - Gauss Central Difference Formulae - Lagrange’s Interpolation formulae- B. Spline interpolation, Cubic spline. Unit-V Curve Fitting: Fitting a straight line - Second degree curve - Exponential curve - Curve fitting & Power curve by method of least squares. Numerical Numerical Integration: Numerical Differentiation-Simpson’s 3/8 Rule, Gaussian Integration Integration, Evaluation of Principal value integrals, Generalized Quadrature. Unit-VI Solution by Taylor’s s - Picard’s serie Method of successive approximation - Euler’s Numerical Method -Runge kutta Methods, Predictor Corrector Methods, Adams- Bashforth solution of ODE Method. Determination of Fourier coefficients - Fourier series-even and odd functions - Unit-VII Fourier series in an arbitrary interval - Even and odd periodic continuation - Half- Fourier Series range Fourier sine and cosine expansions. Unit-VIII Introduction and formation of PDE by elimination of arbitrary constants and Partial arbitrary functions - Solutions of first order linear equation - Non linear equations - Differential Method of separation of variables for second order equations - Two dimensional Equations wave equation.
  • 3. CONTENTS UNIT-V NUMERICAL DIFFERENTIATION & INTEGRATION  Numerical Differentiation  Numerical Integration  Trapezoidal Rule  Simpson’s 1/3 Rule  Simpson’s 3/8 Rule
  • 4. Numerical Differentiation and Integration Numerical Differentiation Equally Spaced Arguments Aim: We want to calculate at the tabulated points. The intention of Using these formulas is that, without finding the polynomial for the given curve, we will find its first, second, third, . . . derivatives. Since Arguments are equally spaced, we can use Forward, Backward or Central differences. Differentiation using Forward Differences We know that By Taylor’s Series expansion, we have Define so that , Now, Taking Log on both sides, we get To find Second Derivative We have
  • 5. Squaring on both sides, we get ( ) To find Third Derivative We have Cubing on both sides, we get Differentiation using Backward differences We know that By Taylor’s Series expansion, we have Define so that , Now,
  • 6. Taking Log on both sides, we get To find Second Derivative We have Squaring on both sides, we get ( ) To find Third Derivative We have Cubing on both sides, we get Differentiation using Central differences We know that the Stirling’s Formula is given by
  • 7. Where Now, Differentiating w.r.t. , we get At Similarly, When we have to use these formulae? When we are asked to find at the point , the problem analyzing should be as follows: If the point is nearer to the starting arguments of the given table, then use Forward difference formulas for differentiation If the point is nearer to the ending arguments of the given table, then use Backward difference formulas for differentiation If the point is nearer to the Middle arguments of the given table, then use Central difference formulas for differentiation. Numerical Integration We know that a definite integral of the form represents the area under the curve , enclosed between the limits and . Let . Here the value of is a Numerical value. Aim: To find the approximation to the Numerical value of . The process of finding the approximation to the definite Integral is known as Numerical Integration. Let be given set of observations, and let be the corresponding values for the curve . This formulae is also known as Newton Cotes closed type Formulae. If , the formula is known as Trapezoidal Rule If , the formula is known as Simpson’s Rule
  • 8. If , the formula is known as Simpson’s Rule Trapezoidal Rule i.e. Here is number of Intervals, and Simpson’s Rule i.e. Simpson’s Rule i.e. 2( ℎℎ 3) If Even number of Intervals are there, it is preferred to use Simpson’s Rule (Or) Trapezoidal Rule. If Number of Intervals is multiple of 3, then use Simpson’s Rule (Or) Trapezoidal Rule. If Odd number of Intervals are there, and which is not multiple of 3, then use Trapezoidal Rule. Ex: 5, 7 etc. For any number of Intervals, the default Rule we can use is Trapezoidal.