Finite Difference Formulae for Unequal Sub- Intervals Using Lagrange s Interpolation Formula

Size: px
Start display at page:

Download "Finite Difference Formulae for Unequal Sub- Intervals Using Lagrange s Interpolation Formula"

Transcription

1 Int. Journal o Mat. Analyi, Vol., 9, no. 7, Finite Dierence Formulae or Unequal Sub- Interval Uing Lagrange Interpolation Formula Aok K. Sing a and B. S. Badauria b Department o Matematic, Faculty o Science, Banara indu Univerity, Varanai-5, India a aok@bu.ac.in, b drbbadauria@yaoo.com Abtract General inite dierence ormulae and te correponding error term ave been derived conidering unequally paced grid point, and uing Lagrange interpolation ormula. Furter te inite dierence ormulae and te error term or equally paced ub-interval ave alo been obtained a pecial cae o te preent tudy. Matematic Subject Claiication: Primary 5D, Secondary 5D5 Keyword: Finite dierence ormulae, Lagrange interpolation ormula, Error term, Clamped Simpon rule. Introduction Finite dierence metod i one o te very eective metod ued or olving te dierential equation ordinary or partial numerically. It involve replacing te derivative appearing in te dierential equation and boundary condition by uitable inite dierence approimation. Te accuracy o te olution depend upon te number o grid point, coen. By increaing te number o grid point one can increae te accuracy o te olution to a deire degree, owever it involve increaingly tediou matematical analyi. Baed on Tayor erie, Kan and Oba [-8] preented ome new dierence ceme or inite dierence approimation. Tey obtained cloed-

2 8 Aok K. Sing and B. S. Badauria orm epreion o tee new dierence ormulae, wic can give approimation o arbitrary order. Recently, uing Lagrange interpolation ormula, Sing and Torpe [9] ave given a general metod rom wic variou type o inite dierence ormulae can be obtained by aigning te uitable value to te parameter. Furter te metod alo acilitate te generation o inite dierence ormulae or iger derivative by dierentiation. owever te applicability o te above metod appear to be limited a teir metod old only wen te grid point are equally paced. Anoter cla o problem concerned wit te inite dierence ormulae in te numerical analyi i to ind tem in cae o unequal ubinterval. Ti ituation pecially arie in te matematical modelling wen te unction a been obtained eperimentally and te independent variable i not under te control o te eperimenter, tu one need to ind te inite dierence ormulae or te obervational data. To tackle ti ituation, by introducing generalized Vandermonde determinant, Li [] preented general eplicit dierence ormulae wit arbitrary order accuracy or approimating irt and iger order derivative, wic can be ued or bot equally and unequally paced data. owever, we ue te available Lagrange interpolation ormula to obtain te inite dierence ormulae or unequally paced ubinterval.. Analyi Uing te Lagrange interpolation ormula, unction can be epreed a[] were tand or j j n l j j j, wile l j i a given below l j π π j j. In te above equation, prime denote dierentiation wit repect to and.... π. Te truncation error, in te evaluation o i a given below: n

3 Finite dierence ormulae 87 E n π n! n ξ n were ξ denote n t derivative o ξ interval[, ]. Te interval [, ] n widt,,, n, wile ξ lie between te be divided into n ubinterval o unequal n n n i i..., uc tat. a Tree Point Finite dierence ormulae: For ti cae n, and ence etting, and 5 in equation we ave epreion or a. Dierentiating equation wit repect to, we get. 7 Ten by putting repectively,, derivative o and /, te ormulae or te irt order at te point,, can be obtained a, 8a, 8b and. 8c

4 88 Aok K. Sing and B. S. Badauria Uing 5 in equation, te error term ave been calculated a ollow E ξ 9. and E ξ Te correponding error term in te ormulae 8a, b, c or, and /, ξ ξ ξ. reult in repectively a, and Dierentiation o equation 7 produce dierence ormula or econd derivative a [ ], and te correponding error term can be obtained by dierentiating equation. For, we obtain te inite dierence ormulae and te correponding truncation error or equal ub-interval a obtained by Sing and Torpe [9]. b Four point inite dierence ormulae: In ti cae n, and ubtituting Sing and Torpe[],, and in te correponding equation o, we get were. Dierentiation o produce

5 Finite dierence ormulae 89. For /,, and /, te repective inite dierence ormulae are obtained rom a ollow:, 5a, 5b, 5c. 5d Te aociated error term or our point ormula i obtained rom equation a

6 8 Aok K. Sing and B. S. Badauria { } [ ] ξ iv E. Te truncation error correponding to equation 5a, b, c, d are derived repectively, rom equation a [,,, ] / ξ iv. Dierentiation o equation give dierence ormulae correponding to te econd derivative a. 7 For /,, and /, epreion 7 reult in, 8a, 8b, 8c and

7 Finite dierence ormulae 8, 8d repectively. Truncation error concerned wit equation 7 i obtained rom dierentiation o equation a { } [ ] ξ iv E 5, 9 rom wic repective truncation error correponding to equation 8 can be derived. Dierentiation o equation 7 give wic i te dierence ormula or te tird derivative in term o te unction at te our point ituated at unequal interval. Te correponding truncation error can be obtained by dierentiating equation 9. Putting in above epreion, we obtained te reult or equal ub-interval a obtained by Sing and Torpe [9]. c Five point inite dierence ormulae: Te value o n i our or ive point dierence ormulae. Subtituting,,,, in te correponding equation obtained rom, and ten dierentiating te reulting equation, we get

8 8 Aok K. Sing and B. S. Badauria Te epreion or te above derivative at and, are obtained by etting repectively, /, and / : and, 5

9 Finite dierence ormulae 8 were. Alo te truncation error correponding to - 5 are a given below: ξ v E ξ v E 7 and ξ v E 8 Te econd and tird order derivative o te unction at, and are, 9

10 8 Aok K. Sing and B. S. Badauria,,,.

11 Finite dierence ormulae 85 Equation 9- repreent te orward, central and backward dierence ormulae wic are widely ued to approimate te derivative in practice. Alo te ourt order derivative i given by iv. 5 Te truncation error correponding to 9-5 can be obtained by dierentiating, a obtained in -8 correponding to -5. A particular cae, i we put in te above epreion 9-5, we obtained te reult or equal ub-interval a given below 5 5 a b 5 5 c 8 5 d e 5 8 and iv, g

12 8 Aok K. Sing and B. S. Badauria wic are eactly ame a obtained by Sing and Torpe [9]. Formulation o te above inite dierence approimation clearly ugget tat te inite dierence ormulae in term o any number o point can be obtained wit te elp o equation and. Te matematical epreion reulting due to urter dierentiation o equation will give inite dierence ormulae or iger derivative.. Concluion ere we ave preented,, and 5 point eplicit inite dierence ormulae along wit te error term, or approimating te irt and iger order derivative or unequally paced data. By dierentiating te equation, inite dierence ormulae or iger order derivative can alo be obtained. Tee ormulae can be ued directly to olve te ordinary and partial dierential equation and will erve to approimate te derivative at te unequally paced grid point. A cientiic program o te above ormulae will acilitate te ue o any inite dierence ormulae o deired derivative. Acknowledgment. Autor would like to tank te Centre or Interdiciplinary Matematical Science, Banara indu Univerity, Varanai-5, or providing te inancial aitance and oter acilitie. Reerence [] F. B. ildebrand, Introduction to Numerical Analyi, Mc Graw ill, Inc, New York, 97. [] Jianping Li, General eplicit dierence ormula or numerical dierentiation, J. Comput. Appl. Mat., 8 5, 9 5. [] I. R. Kan and R. Oba, Cloed-orm epreion or te inite dierence approimation o irt and iger derivative baed on Taylor erie, J. Comput. Appl.Mat., 7 999a, [] I. R. Kan and R. Oba, Digital dierentiator baed on Taylor erie, IEICE Tran. Fund. E8-A, 999b, 8 8.

13 Finite dierence ormulae 87 [5] I. R. Kan and R. Oba, New inite dierence ormula or numerical dierentiation, J. Comput. Appl. Mat.,, 9 7. [] I. R. Kan and R. Oba, Matematical proo o eplicit ormula or tapcoeicient o Taylor erie baed FIR digital dierentiator, IEICE Tran.Fund.E8- A,, [7] I. R. Kan and R. Oba, Taylor erie baed inite dierence approimation o iger-degree derivative, J. Comput. Appl. Mat., 5 a, 5. [8] I. R. Kan, R. Oba and N. ozumi, Matematical proo o cloed orm epreion or inite dierence approimation baed on Taylor erie, J. Comput. Appl. Mat., 5 b, -9. [9] A. K. Sing and G. R. Torpe, Finite dierence ormulae rom Lagrange interpolation ormula, J. Scientiic Reearc, 5 8, -7. [] A. K. Sing and G. R. Torpe, Simpon /-rule o integration or unequal diviion o integration domain, J. Concrete Applicable Mat.,, 7-5. Received: September, 8

On The Approximate Solution of Linear Fuzzy Volterra-Integro Differential Equations of the Second Kind

On The Approximate Solution of Linear Fuzzy Volterra-Integro Differential Equations of the Second Kind AUSTRALIAN JOURNAL OF BASIC AND APPLIED SCIENCES ISSN:99-878 EISSN: 39-8 Journal ome page: www.ajbaweb.com On Te Approimate Solution of Linear Fuzzy Volterra-Integro Differential Equation of te Second

More information

Taylor Series and the Mean Value Theorem of Derivatives

Taylor Series and the Mean Value Theorem of Derivatives 1 - Taylor Series and te Mean Value Teorem o Derivatives Te numerical solution o engineering and scientiic problems described by matematical models oten requires solving dierential equations. Dierential

More information

Numerical Differentiation

Numerical Differentiation Numerical Differentiation Finite Difference Formulas for te first derivative (Using Taylor Expansion tecnique) (section 8.3.) Suppose tat f() = g() is a function of te variable, and tat as 0 te function

More information

Computer Derivations of Numerical Differentiation Formulae. Int. J. of Math. Education in Sci. and Tech., V 34, No 2 (March-April 2003), pp

Computer Derivations of Numerical Differentiation Formulae. Int. J. of Math. Education in Sci. and Tech., V 34, No 2 (March-April 2003), pp Computer Derivations o Numerical Dierentiation Formulae By Jon H. Matews Department o Matematics Caliornia State University Fullerton USA Int. J. o Mat. Education in Sci. and Tec. V No (Marc-April ) pp.8-87.

More information

Inference for Two Stage Cluster Sampling: Equal SSU per PSU. Projections of SSU Random Variables on Each SSU selection.

Inference for Two Stage Cluster Sampling: Equal SSU per PSU. Projections of SSU Random Variables on Each SSU selection. Inference for Two Stage Cluter Sampling: Equal SSU per PSU Projection of SSU andom Variable on Eac SSU election By Ed Stanek Introduction We review etimating equation for PSU mean in a two tage cluter

More information

Continuity and Differentiability

Continuity and Differentiability Continuity and Dierentiability Tis capter requires a good understanding o its. Te concepts o continuity and dierentiability are more or less obvious etensions o te concept o its. Section - INTRODUCTION

More information

Intermediate Math Circles November 5, 2008 Geometry II

Intermediate Math Circles November 5, 2008 Geometry II 1 Univerity of Waterloo Faculty of Matematic Centre for Education in Matematic and Computing Intermediate Mat Circle November 5, 2008 Geometry II Geometry 2-D Figure Two-dimenional ape ave a perimeter

More information

DIFFERENTIAL POLYNOMIALS GENERATED BY SECOND ORDER LINEAR DIFFERENTIAL EQUATIONS

DIFFERENTIAL POLYNOMIALS GENERATED BY SECOND ORDER LINEAR DIFFERENTIAL EQUATIONS Journal o Applied Analysis Vol. 14, No. 2 2008, pp. 259 271 DIFFERENTIAL POLYNOMIALS GENERATED BY SECOND ORDER LINEAR DIFFERENTIAL EQUATIONS B. BELAÏDI and A. EL FARISSI Received December 5, 2007 and,

More information

OBSERVER-BASED REDUCED ORDER CONTROLLER DESIGN FOR THE STABILIZATION OF LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS

OBSERVER-BASED REDUCED ORDER CONTROLLER DESIGN FOR THE STABILIZATION OF LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS International Journal o Computer Science, Engineering and Inormation Technology (IJCSEIT, Vol.1, No.5, December 2011 OBSERVER-BASED REDUCED ORDER CONTROLLER DESIGN FOR THE STABILIZATION OF LARGE SCALE

More information

On One Justification on the Use of Hybrids for the Solution of First Order Initial Value Problems of Ordinary Differential Equations

On One Justification on the Use of Hybrids for the Solution of First Order Initial Value Problems of Ordinary Differential Equations Pure and Applied Matematics Journal 7; 6(5: 74 ttp://wwwsciencepublisinggroupcom/j/pamj doi: 648/jpamj765 ISSN: 6979 (Print; ISSN: 698 (Online On One Justiication on te Use o Hybrids or te Solution o First

More information

A class of multiattribute utility functions

A class of multiattribute utility functions Economic Teory DOI 10.1007/00199-007-0207-x EXPOSITA NOTE Andrá Prékopa Gergely Mádi-Nagy A cla of multiattribute utility function Received: 25 July 2005 / Revied: 8 January 2007 Springer-Verlag 2007 Abtract

More information

Hilbert-Space Integration

Hilbert-Space Integration Hilbert-Space Integration. Introduction. We often tink of a PDE, like te eat equation u t u xx =, a an evolution equation a itorically wa done for ODE. In te eat equation example two pace derivative are

More information

Exact Solutions for Fixed-Fixed Anisotropic Beams under Uniform Load by Using Maple

Exact Solutions for Fixed-Fixed Anisotropic Beams under Uniform Load by Using Maple Eact Solution for Fied-Fied Aniotropic Beam under Uniform Load b Uing Maple Department of Civil Engineering, Ho Ci Min Cit Univerit of Arcitecture, Vietnam ABSTRACT Te approimate olution of tree and diplacement

More information

LECTURE 14 NUMERICAL INTEGRATION. Find

LECTURE 14 NUMERICAL INTEGRATION. Find LECTURE 14 NUMERCAL NTEGRATON Find b a fxdx or b a vx ux fx ydy dx Often integration is required. However te form of fx may be suc tat analytical integration would be very difficult or impossible. Use

More information

Velocity or 60 km/h. a labelled vector arrow, v 1

Velocity or 60 km/h. a labelled vector arrow, v 1 11.7 Velocity en you are outide and notice a brik wind blowing, or you are riding in a car at 60 km/, you are imply conidering te peed of motion a calar quantity. ometime, owever, direction i alo important

More information

A High Throughput String Matching Architecture for Intrusion Detection and Prevention

A High Throughput String Matching Architecture for Intrusion Detection and Prevention A Hig Trougput tring Matcing Arcitecture for Intruion Detection and Prevention Lin Tan, Timoty erwood Appeared in ICA 25 Preented by: aile Kumar Dicuion Leader: Max Podleny Overview Overview of ID/IP ytem»

More information

CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS

CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS CHAPTER 8 OBSERVER BASED REDUCED ORDER CONTROLLER DESIGN FOR LARGE SCALE LINEAR DISCRETE-TIME CONTROL SYSTEMS 8.1 INTRODUCTION 8.2 REDUCED ORDER MODEL DESIGN FOR LINEAR DISCRETE-TIME CONTROL SYSTEMS 8.3

More information

Manprit Kaur and Arun Kumar

Manprit Kaur and Arun Kumar CUBIC X-SPLINE INTERPOLATORY FUNCTIONS Manprit Kaur and Arun Kumar manpreet2410@gmail.com, arun04@rediffmail.com Department of Mathematic and Computer Science, R. D. Univerity, Jabalpur, INDIA. Abtract:

More information

This appendix derives Equations (16) and (17) from Equations (12) and (13).

This appendix derives Equations (16) and (17) from Equations (12) and (13). Capital growt pat of te neoclaical growt model Online Supporting Information Ti appendix derive Equation (6) and (7) from Equation () and (3). Equation () and (3) owed te evolution of pyical and uman capital

More information

Numerical Analysis MTH603. dy dt = = (0) , y n+1. We obtain yn. Therefore. and. Copyright Virtual University of Pakistan 1

Numerical Analysis MTH603. dy dt = = (0) , y n+1. We obtain yn. Therefore. and. Copyright Virtual University of Pakistan 1 Numerical Analysis MTH60 PREDICTOR CORRECTOR METHOD Te metods presented so far are called single-step metods, were we ave seen tat te computation of y at t n+ tat is y n+ requires te knowledge of y n only.

More information

A Constraint Propagation Algorithm for Determining the Stability Margin. The paper addresses the stability margin assessment for linear systems

A Constraint Propagation Algorithm for Determining the Stability Margin. The paper addresses the stability margin assessment for linear systems A Contraint Propagation Algorithm for Determining the Stability Margin of Linear Parameter Circuit and Sytem Lubomir Kolev and Simona Filipova-Petrakieva Abtract The paper addree the tability margin aement

More information

ch (for some fixed positive number c) reaching c

ch (for some fixed positive number c) reaching c GSTF Journal of Matematics Statistics and Operations Researc (JMSOR) Vol. No. September 05 DOI 0.60/s4086-05-000-z Nonlinear Piecewise-defined Difference Equations wit Reciprocal and Cubic Terms Ramadan

More information

AMS 147 Computational Methods and Applications Lecture 09 Copyright by Hongyun Wang, UCSC. Exact value. Effect of round-off error.

AMS 147 Computational Methods and Applications Lecture 09 Copyright by Hongyun Wang, UCSC. Exact value. Effect of round-off error. Lecture 09 Copyrigt by Hongyun Wang, UCSC Recap: Te total error in numerical differentiation fl( f ( x + fl( f ( x E T ( = f ( x Numerical result from a computer Exact value = e + f x+ Discretization error

More information

MATH1901 Differential Calculus (Advanced)

MATH1901 Differential Calculus (Advanced) MATH1901 Dierential Calculus (Advanced) Capter 3: Functions Deinitions : A B A and B are sets assigns to eac element in A eactl one element in B A is te domain o te unction B is te codomain o te unction

More information

Fringe integral equations for the 2-D wedges with soft and hard boundaries. r Fringe Wave Integral Equation

Fringe integral equations for the 2-D wedges with soft and hard boundaries. r Fringe Wave Integral Equation RESEARCH ARTICLE Key Point: An alternative approac baed on te integral euation derived directly for tefringecurrentipreented A MoM-baed algoritm i developed for direct modeling of fringe wave around oft

More information

SENSITIVITY ANALYSIS FOR COUNTER FLOW COOLING TOWER- PART I, EXIT COLD WATER TEMPERATURE

SENSITIVITY ANALYSIS FOR COUNTER FLOW COOLING TOWER- PART I, EXIT COLD WATER TEMPERATURE SENSITIVITY ANALYSIS FOR COUNTER FLOW COOLING TOWER- PART I, EXIT COLD WATER TEMPERATURE *Citranjan Agaral Department of Mecanical Engineering, College of Tecnology and Engineering, Maarana Pratap Univerity

More information

Solving Second Order Linear Dirichlet and Neumann Boundary Value Problems by Block Method

Solving Second Order Linear Dirichlet and Neumann Boundary Value Problems by Block Method IAENG International Journal o Applied Matematics 43: IJAM_43 04 Solving Second Order Linear Diriclet and Neumann Boundar Value Problems b Block Metod Zanaria Abdul Majid Mod Mugti Hasni and Norazak Senu

More information

Active Vibration Control Experiments on an. AgustaWestland W30 Helicopter Airframe

Active Vibration Control Experiments on an. AgustaWestland W30 Helicopter Airframe Active Vibration Control Experiment on an AgutaWetland W30 Helicopter Airrame Jon E Motteread, Maryam Gandci Terani, Simon Jame and Peter Court 3 Centre or Engineering Dynamic, Univerity o Liverpool L69

More information

General Solution of the Stress Potential Function in Lekhnitskii s Elastic Theory for Anisotropic and Piezoelectric Materials

General Solution of the Stress Potential Function in Lekhnitskii s Elastic Theory for Anisotropic and Piezoelectric Materials dv. Studies Teor. Pys. Vol. 007 no. 8 7 - General Solution o te Stress Potential Function in Lenitsii s Elastic Teory or nisotropic and Pieoelectric Materials Zuo-en Ou StateKey Laboratory o Explosion

More information

A Class of Linearly Implicit Numerical Methods for Solving Stiff Ordinary Differential Equations

A Class of Linearly Implicit Numerical Methods for Solving Stiff Ordinary Differential Equations The Open Numerical Method Journal, 2010, 2, 1-5 1 Open Acce A Cla o Linearl Implicit Numerical Method or Solving Sti Ordinar Dierential Equation S.S. Filippov * and A.V. Tglian Keldh Intitute o Applied

More information

Consider a function f we ll specify which assumptions we need to make about it in a minute. Let us reformulate the integral. 1 f(x) dx.

Consider a function f we ll specify which assumptions we need to make about it in a minute. Let us reformulate the integral. 1 f(x) dx. Capter 2 Integrals as sums and derivatives as differences We now switc to te simplest metods for integrating or differentiating a function from its function samples. A careful study of Taylor expansions

More information

Fall 2014 MAT 375 Numerical Methods. Numerical Differentiation (Chapter 9)

Fall 2014 MAT 375 Numerical Methods. Numerical Differentiation (Chapter 9) Fall 2014 MAT 375 Numerical Metods (Capter 9) Idea: Definition of te derivative at x Obviuos approximation: f (x) = lim 0 f (x + ) f (x) f (x) f (x + ) f (x) forward-difference formula? ow good is tis

More information

Conductance from Transmission Probability

Conductance from Transmission Probability Conductance rom Transmission Probability Kelly Ceung Department o Pysics & Astronomy University o Britis Columbia Vancouver, BC. Canada, V6T1Z1 (Dated: November 5, 005). ntroduction For large conductors,

More information

IGC. 50 th. 50 th INDIAN GEOTECHNICAL CONFERENCE SEISMIC ACTIVE EARTH PRESSURE ON RETAINING WALL CONSIDERING SOIL AMPLIFICATION

IGC. 50 th. 50 th INDIAN GEOTECHNICAL CONFERENCE SEISMIC ACTIVE EARTH PRESSURE ON RETAINING WALL CONSIDERING SOIL AMPLIFICATION INDIAN GEOTECHNICAL CONFERENCE SEISMIC ACTIVE EARTH PRESSURE ON RETAINING WALL CONSIDERING SOIL AMPLIFICATION Obaidur Raaman 1 and Priati Raycowdury 2 ABSTRACT Te quet for te realitic etimation of eimic

More information

Design of Robust PI Controller for Counter-Current Tubular Heat Exchangers

Design of Robust PI Controller for Counter-Current Tubular Heat Exchangers Deign of Robut PI Controller for Counter-Current Tubular Heat Excanger Jana Závacká Monika Bakošová Intitute of Information Engineering Automation Matematic Faculty of Cemical Food Tecnology STU in Bratilava

More information

DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science

DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Mathematics and Computer Science DELFT UNIVERSITY OF TECHNOLOGY Faculty of Electrical Engineering, Matematics and Computer Science. ANSWERS OF THE TEST NUMERICAL METHODS FOR DIFFERENTIAL EQUATIONS (WI3097 TU) Tuesday January 9 008, 9:00-:00

More information

Derivation of Some Results on the Generalized Relative Orders of Meromorphic Functions

Derivation of Some Results on the Generalized Relative Orders of Meromorphic Functions DOI: 10.1515/awutm-2017-0004 Analele Universităţii de Vest, Timişoara Seria Matematică Inormatică LV, 1, 2017), 51 61 Derivation o Some Results on te Generalized Relative Orders o Meromorpic Functions

More information

Math 212-Lecture 9. For a single-variable function z = f(x), the derivative is f (x) = lim h 0

Math 212-Lecture 9. For a single-variable function z = f(x), the derivative is f (x) = lim h 0 3.4: Partial Derivatives Definition Mat 22-Lecture 9 For a single-variable function z = f(x), te derivative is f (x) = lim 0 f(x+) f(x). For a function z = f(x, y) of two variables, to define te derivatives,

More information

lecture 26: Richardson extrapolation

lecture 26: Richardson extrapolation 43 lecture 26: Ricardson extrapolation 35 Ricardson extrapolation, Romberg integration Trougout numerical analysis, one encounters procedures tat apply some simple approximation (eg, linear interpolation)

More information

Approximate Analytical Solution for Quadratic Riccati Differential Equation

Approximate Analytical Solution for Quadratic Riccati Differential Equation Iranian J. of Numerical Analyi and Optimization Vol 3, No. 2, 2013), pp 21-31 Approximate Analytical Solution for Quadratic Riccati Differential Equation H. Aminikhah Abtract In thi paper, we introduce

More information

Tangent Lines-1. Tangent Lines

Tangent Lines-1. Tangent Lines Tangent Lines- Tangent Lines In geometry, te tangent line to a circle wit centre O at a point A on te circle is defined to be te perpendicular line at A to te line OA. Te tangent lines ave te special property

More information

lim 1 lim 4 Precalculus Notes: Unit 10 Concepts of Calculus

lim 1 lim 4 Precalculus Notes: Unit 10 Concepts of Calculus Syllabus Objectives: 1.1 Te student will understand and apply te concept of te limit of a function at given values of te domain. 1. Te student will find te limit of a function at given values of te domain.

More information

Non-Computability of Consciousness

Non-Computability of Consciousness NeuroQuantolog December 2007 Vol 5 Iue 4 Page 382-39 Song D. Non-computabilit of concioune 382 Original Article Non-Computabilit of Concioune Daegene Song Abtract Wit te great ucce in imulating man intelligent

More information

GROWTH ANALYSIS OF ENTIRE FUNCTIONS OF TWO COMPLEX VARIABLES

GROWTH ANALYSIS OF ENTIRE FUNCTIONS OF TWO COMPLEX VARIABLES Sa Communications in Matematical Analysis (SCMA Vol. 3 No. 2 (2016 13-24 ttp://scma.marae.ac.ir GROWTH ANALYSIS OF ENTIRE FUNCTIONS OF TWO COMPLEX VARIABLES SANJIB KUMAR DATTA 1 AND TANMAY BISWAS 2 Abstract.

More information

Material for Difference Quotient

Material for Difference Quotient Material for Difference Quotient Prepared by Stepanie Quintal, graduate student and Marvin Stick, professor Dept. of Matematical Sciences, UMass Lowell Summer 05 Preface Te following difference quotient

More information

INTRODUCTION AND MATHEMATICAL CONCEPTS

INTRODUCTION AND MATHEMATICAL CONCEPTS Capter 1 INTRODUCTION ND MTHEMTICL CONCEPTS PREVIEW Tis capter introduces you to te basic matematical tools for doing pysics. You will study units and converting between units, te trigonometric relationsips

More information

Lecture 21. Numerical differentiation. f ( x+h) f ( x) h h

Lecture 21. Numerical differentiation. f ( x+h) f ( x) h h Lecture Numerical differentiation Introduction We can analytically calculate te derivative of any elementary function, so tere migt seem to be no motivation for calculating derivatives numerically. However

More information

Section 3.1: Derivatives of Polynomials and Exponential Functions

Section 3.1: Derivatives of Polynomials and Exponential Functions Section 3.1: Derivatives of Polynomials and Exponential Functions In previous sections we developed te concept of te derivative and derivative function. Te only issue wit our definition owever is tat it

More information

The Laplace equation, cylindrically or spherically symmetric case

The Laplace equation, cylindrically or spherically symmetric case Numerisce Metoden II, 7 4, und Übungen, 7 5 Course Notes, Summer Term 7 Some material and exercises Te Laplace equation, cylindrically or sperically symmetric case Electric and gravitational potential,

More information

University Mathematics 2

University Mathematics 2 University Matematics 2 1 Differentiability In tis section, we discuss te differentiability of functions. Definition 1.1 Differentiable function). Let f) be a function. We say tat f is differentiable at

More information

Multi-dimensional Fuzzy Euler Approximation

Multi-dimensional Fuzzy Euler Approximation Mathematica Aeterna, Vol 7, 2017, no 2, 163-176 Multi-dimenional Fuzzy Euler Approximation Yangyang Hao College of Mathematic and Information Science Hebei Univerity, Baoding 071002, China hdhyywa@163com

More information

These errors are made from replacing an infinite process by finite one.

These errors are made from replacing an infinite process by finite one. Introduction :- Tis course examines problems tat can be solved by metods of approximation, tecniques we call numerical metods. We begin by considering some of te matematical and computational topics tat

More information

Chapter 8. Numerical Solution of Ordinary Differential Equations. Module No. 2. Predictor-Corrector Methods

Chapter 8. Numerical Solution of Ordinary Differential Equations. Module No. 2. Predictor-Corrector Methods Numerical Analysis by Dr. Anita Pal Assistant Professor Department of Matematics National Institute of Tecnology Durgapur Durgapur-7109 email: anita.buie@gmail.com 1 . Capter 8 Numerical Solution of Ordinary

More information

Parameter Fitted Scheme for Singularly Perturbed Delay Differential Equations

Parameter Fitted Scheme for Singularly Perturbed Delay Differential Equations International Journal of Applied Science and Engineering 2013. 11, 4: 361-373 Parameter Fitted Sceme for Singularly Perturbed Delay Differential Equations Awoke Andargiea* and Y. N. Reddyb a b Department

More information

Derivatives of Exponentials

Derivatives of Exponentials mat 0 more on derivatives: day 0 Derivatives of Eponentials Recall tat DEFINITION... An eponential function as te form f () =a, were te base is a real number a > 0. Te domain of an eponential function

More information

N igerian Journal of M athematics and Applications V olume 23, (2014), 1 13

N igerian Journal of M athematics and Applications V olume 23, (2014), 1 13 N igerian Journal of M atematics and Applications V olume 23, (24), 3 c N ig. J. M at. Appl. ttp : //www.kwsman.com CONSTRUCTION OF POLYNOMIAL BASIS AND ITS APPLICATION TO ORDINARY DIFFERENTIAL EQUATIONS

More information

232 Calculus and Structures

232 Calculus and Structures 3 Calculus and Structures CHAPTER 17 JUSTIFICATION OF THE AREA AND SLOPE METHODS FOR EVALUATING BEAMS Calculus and Structures 33 Copyrigt Capter 17 JUSTIFICATION OF THE AREA AND SLOPE METHODS 17.1 THE

More information

Solving Continuous Linear Least-Squares Problems by Iterated Projection

Solving Continuous Linear Least-Squares Problems by Iterated Projection Solving Continuous Linear Least-Squares Problems by Iterated Projection by Ral Juengling Department o Computer Science, Portland State University PO Box 75 Portland, OR 977 USA Email: juenglin@cs.pdx.edu

More information

arxiv:nucl-th/ v1 20 Oct 2005

arxiv:nucl-th/ v1 20 Oct 2005 International Journal of Modern yic E c World cientific ubliing Company arxiv:nucl-t/55v1 ct 5 ARREE-FCK-BGLYUBV CALCULAIN FR NUCLEI WI ERAEDRAL DEFRMAIN. LBRAWKI and J. DBACZEWKI Intitute of eoretical

More information

Order of Accuracy. ũ h u Ch p, (1)

Order of Accuracy. ũ h u Ch p, (1) Order of Accuracy 1 Terminology We consider a numerical approximation of an exact value u. Te approximation depends on a small parameter, wic can be for instance te grid size or time step in a numerical

More information

LEARNING FROM MISTAKES

LEARNING FROM MISTAKES AP Central Quetion of te Mont May 3 Quetion of te Mont By Lin McMullin LEARNING FROM MISTAKES Ti i te firt Quetion of te Mont tat ill appear on te Calculu ection of AP Central. Tee are not AP Exam quetion,

More information

Combining functions: algebraic methods

Combining functions: algebraic methods Combining functions: algebraic metods Functions can be added, subtracted, multiplied, divided, and raised to a power, just like numbers or algebra expressions. If f(x) = x 2 and g(x) = x + 2, clearly f(x)

More information

Simulation and verification of a plate heat exchanger with a built-in tap water accumulator

Simulation and verification of a plate heat exchanger with a built-in tap water accumulator Simulation and verification of a plate eat excanger wit a built-in tap water accumulator Anders Eriksson Abstract In order to test and verify a compact brazed eat excanger (CBE wit a built-in accumulation

More information

Physics 41 Homework Set 3 Chapter 17 Serway 7 th Edition

Physics 41 Homework Set 3 Chapter 17 Serway 7 th Edition Pyic 41 Homework Set 3 Capter 17 Serway 7 t Edition Q: 1, 4, 5, 6, 9, 1, 14, 15 Quetion *Q17.1 Anwer. Te typically iger denity would by itelf make te peed of ound lower in a olid compared to a ga. Q17.4

More information

Chapter 2 Limits and Continuity. Section 2.1 Rates of Change and Limits (pp ) Section Quick Review 2.1

Chapter 2 Limits and Continuity. Section 2.1 Rates of Change and Limits (pp ) Section Quick Review 2.1 Section. 6. (a) N(t) t (b) days: 6 guppies week: 7 guppies (c) Nt () t t t ln ln t ln ln ln t 8. 968 Tere will be guppies ater ln 8.968 days, or ater nearly 9 days. (d) Because it suggests te number o

More information

1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point

1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point MA00 Capter 6 Calculus and Basic Linear Algebra I Limits, Continuity and Differentiability Te concept of its (p.7 p.9, p.4 p.49, p.55 p.56). Limits Consider te function determined by te formula f Note

More information

Section 15.6 Directional Derivatives and the Gradient Vector

Section 15.6 Directional Derivatives and the Gradient Vector Section 15.6 Directional Derivatives and te Gradient Vector Finding rates of cange in different directions Recall tat wen we first started considering derivatives of functions of more tan one variable,

More information

8-4 P 2. = 12 kw. AIR T = const. Therefore, Q &

8-4 P 2. = 12 kw. AIR T = const. Therefore, Q & 8-4 8-4 Air i compreed teadily by a compreor. e air temperature i mataed contant by eat rejection to te urroundg. e rate o entropy cange o air i to be determed. Aumption i i a teady-low proce ce tere i

More information

High Coupling Factor Piezoelectric Materials for Bending Actuators: Analytical and Finite Elements Modeling Results

High Coupling Factor Piezoelectric Materials for Bending Actuators: Analytical and Finite Elements Modeling Results Excerpt from te Proceeding of te COSOL Conference 009 ilan Hig Coupling Factor Pieoelectric aterial for Bending Actuator: Analytical and Finite Element odeling Reult I.A. Ivan *1,. Rakotondrabe 1 and N.

More information

Introduction to Derivatives

Introduction to Derivatives Introduction to Derivatives 5-Minute Review: Instantaneous Rates and Tangent Slope Recall te analogy tat we developed earlier First we saw tat te secant slope of te line troug te two points (a, f (a))

More information

Honors Calculus Midterm Review Packet

Honors Calculus Midterm Review Packet Name Date Period Honors Calculus Midterm Review Packet TOPICS THAT WILL APPEAR ON THE EXAM Capter Capter Capter (Sections. to.6) STRUCTURE OF THE EXAM Part No Calculators Miture o multiple-coice, matcing,

More information

Reformulation of Block Implicit Linear Multistep Method into Runge Kutta Type Method for Initial Value Problem

Reformulation of Block Implicit Linear Multistep Method into Runge Kutta Type Method for Initial Value Problem International Journal of Science and Technology Volume 4 No. 4, April, 05 Reformulation of Block Implicit Linear Multitep Method into Runge Kutta Type Method for Initial Value Problem Muhammad R., Y. A

More information

The Verlet Algorithm for Molecular Dynamics Simulations

The Verlet Algorithm for Molecular Dynamics Simulations Cemistry 380.37 Fall 2015 Dr. Jean M. Standard November 9, 2015 Te Verlet Algoritm for Molecular Dynamics Simulations Equations of motion For a many-body system consisting of N particles, Newton's classical

More information

CISE-301: Numerical Methods Topic 1:

CISE-301: Numerical Methods Topic 1: CISE-3: Numerical Methods Topic : Introduction to Numerical Methods and Taylor Series Lectures -4: KFUPM Term 9 Section 8 CISE3_Topic KFUPM - T9 - Section 8 Lecture Introduction to Numerical Methods What

More information

Domain Optimization Analysis in Linear Elastic Problems * (Approach Using Traction Method)

Domain Optimization Analysis in Linear Elastic Problems * (Approach Using Traction Method) Domain Optimization Analyi in Linear Elatic Problem * (Approach Uing Traction Method) Hideyuki AZEGAMI * and Zhi Chang WU *2 We preent a numerical analyi and reult uing the traction method for optimizing

More information

Higher Derivatives. Differentiable Functions

Higher Derivatives. Differentiable Functions Calculus 1 Lia Vas Higer Derivatives. Differentiable Functions Te second derivative. Te derivative itself can be considered as a function. Te instantaneous rate of cange of tis function is te second derivative.

More information

Lab 6 Derivatives and Mutant Bacteria

Lab 6 Derivatives and Mutant Bacteria Lab 6 Derivatives and Mutant Bacteria Date: September 27, 20 Assignment Due Date: October 4, 20 Goal: In tis lab you will furter explore te concept of a derivative using R. You will use your knowledge

More information

REPRESENTATION OF ALGEBRAIC STRUCTURES BY BOOLEAN FUNCTIONS. Logic and Applications 2015 (LAP 2015) September 21-25, 2015, Dubrovnik, Croatia

REPRESENTATION OF ALGEBRAIC STRUCTURES BY BOOLEAN FUNCTIONS. Logic and Applications 2015 (LAP 2015) September 21-25, 2015, Dubrovnik, Croatia REPRESENTATION OF ALGEBRAIC STRUCTURES BY BOOLEAN FUNCTIONS SMILE MARKOVSKI Faculty of Computer Science and Engineering, S Ciryl and Methodiu Univerity in Skopje, MACEDONIA mile.markovki@gmail.com Logic

More information

Modeling of the Fluid Solid Interaction during Seismic Event

Modeling of the Fluid Solid Interaction during Seismic Event Journal o Material cience and Enineerin A 5 (3-4) (015) 171-175 doi: 10.1765/161-613/015.3-4.010 D DAVID PIHING Modelin o the luid olid Interaction durin eimic Event Jan Vachulka * tevenon and Aociate,

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL IFFERENTIATION FIRST ERIVATIVES Te simplest difference formulas are based on using a straigt line to interpolate te given data; tey use two data pints to estimate te derivative. We assume tat

More information

NUMBERS. := p n 1 + p n 2 q + p n 3 q pq n 2 + q n 1 = pn q n p q. We can write easily that [n] p,q. , where [n] q/p

NUMBERS. := p n 1 + p n 2 q + p n 3 q pq n 2 + q n 1 = pn q n p q. We can write easily that [n] p,q. , where [n] q/p Kragujevac Journal of Mathematic Volume 424) 2018), Page 555 567 APOSTOL TYPE p, q)-frobenius-euler POLYNOMIALS AND NUMBERS UGUR DURAN 1 AND MEHMET ACIKGOZ 2 Abtract In the preent paper, we introduce p,

More information

Some Results on the Growth Analysis of Entire Functions Using their Maximum Terms and Relative L -orders

Some Results on the Growth Analysis of Entire Functions Using their Maximum Terms and Relative L -orders Journal of Matematical Extension Vol. 10, No. 2, (2016), 59-73 ISSN: 1735-8299 URL: ttp://www.ijmex.com Some Results on te Growt Analysis of Entire Functions Using teir Maximum Terms and Relative L -orders

More information

Differentiation. introduction to limits

Differentiation. introduction to limits 9 9A Introduction to limits 9B Limits o discontinuous, rational and brid unctions 9C Dierentiation using i rst principles 9D Finding derivatives b rule 9E Antidierentiation 9F Deriving te original unction

More information

Parameterized Soft Complex Fuzzy Sets

Parameterized Soft Complex Fuzzy Sets Journal of Progressive Researc in Matematics(JPRM) IN: 95-08 CITECH Volume Issue REERCH ORGNITION Publised online: June 7 05 Journal of Progressive Researc in Matematics www.scitecresearc.com/journals

More information

Reliability Analysis of Embedded System with Different Modes of Failure Emphasizing Reboot Delay

Reliability Analysis of Embedded System with Different Modes of Failure Emphasizing Reboot Delay International Journal of Applied Science and Engineering 3., 4: 449-47 Reliability Analyi of Embedded Sytem with Different Mode of Failure Emphaizing Reboot Delay Deepak Kumar* and S. B. Singh Department

More information

Simultaneous Quadruple Series Equations Involving Lagueree Polynomials

Simultaneous Quadruple Series Equations Involving Lagueree Polynomials Global Journal of Pure and pplied Mathematic. ISSN 973-1768 Volume 13, Number 7 (217), pp. 3773-3778 Reearch India Publication http://www.ripublication.com Simultaneou Quadruple Serie Equation Involving

More information

A Reconsideration of Matter Waves

A Reconsideration of Matter Waves A Reconsideration of Matter Waves by Roger Ellman Abstract Matter waves were discovered in te early 20t century from teir wavelengt, predicted by DeBroglie, Planck's constant divided by te particle's momentum,

More information

One Class of Splitting Iterative Schemes

One Class of Splitting Iterative Schemes One Cla of Splitting Iterative Scheme v Ciegi and V. Pakalnytė Vilniu Gedimina Technical Univerity Saulėtekio al. 11, 2054, Vilniu, Lithuania rc@fm.vtu.lt Abtract. Thi paper deal with the tability analyi

More information

Average Rate of Change

Average Rate of Change Te Derivative Tis can be tougt of as an attempt to draw a parallel (pysically and metaporically) between a line and a curve, applying te concept of slope to someting tat isn't actually straigt. Te slope

More information

Exercises for lectures 20 Digital Control

Exercises for lectures 20 Digital Control Exercie for lecture 0 Digital Control Micael Šebek Automatic control 06-4- Sampling: and z relationip for complex pole Continuou ignal Laplace tranform wit pole Dicrete ignal z-tranform, t y( t) e in t,

More information

1.5 Function Arithmetic

1.5 Function Arithmetic 76 Relations and Functions.5 Function Aritmetic In te previous section we used te newly deined unction notation to make sense o epressions suc as ) + 2 and 2) or a iven unction. It would seem natural,

More information

Effects of Radiation on Unsteady Couette Flow between Two Vertical Parallel Plates with Ramped Wall Temperature

Effects of Radiation on Unsteady Couette Flow between Two Vertical Parallel Plates with Ramped Wall Temperature Volume 39 No. February 01 Effects of Radiation on Unsteady Couette Flow between Two Vertical Parallel Plates wit Ramped Wall Temperature S. Das Department of Matematics University of Gour Banga Malda 73

More information

Symmetry Labeling of Molecular Energies

Symmetry Labeling of Molecular Energies Capter 7. Symmetry Labeling of Molecular Energies Notes: Most of te material presented in tis capter is taken from Bunker and Jensen 1998, Cap. 6, and Bunker and Jensen 2005, Cap. 7. 7.1 Hamiltonian Symmetry

More information

Function Composition and Chain Rules

Function Composition and Chain Rules Function Composition and s James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 8, 2017 Outline 1 Function Composition and Continuity 2 Function

More information

Properties of the Laplace transform on time scales with arbitrary graininess

Properties of the Laplace transform on time scales with arbitrary graininess Integral Tranform and Special Function Vol. 22, No. 11, November 2011, 785 800 Propertie of te Laplace tranform on time cale wit arbitrary grainine Martin Boner a *, Guein S. Gueinov b and Başak Karpuz

More information

Chapter 2 Sampling and Quantization. In order to investigate sampling and quantization, the difference between analog

Chapter 2 Sampling and Quantization. In order to investigate sampling and quantization, the difference between analog Chapter Sampling and Quantization.1 Analog and Digital Signal In order to invetigate ampling and quantization, the difference between analog and digital ignal mut be undertood. Analog ignal conit of continuou

More information

3.1 Extreme Values of a Function

3.1 Extreme Values of a Function .1 Etreme Values of a Function Section.1 Notes Page 1 One application of te derivative is finding minimum and maimum values off a grap. In precalculus we were only able to do tis wit quadratics by find

More information

MATH1151 Calculus Test S1 v2a

MATH1151 Calculus Test S1 v2a MATH5 Calculus Test 8 S va January 8, 5 Tese solutions were written and typed up by Brendan Trin Please be etical wit tis resource It is for te use of MatSOC members, so do not repost it on oter forums

More information

NUMERICAL DIFFERENTIATION. James T. Smith San Francisco State University. In calculus classes, you compute derivatives algebraically: for example,

NUMERICAL DIFFERENTIATION. James T. Smith San Francisco State University. In calculus classes, you compute derivatives algebraically: for example, NUMERICAL DIFFERENTIATION James T Smit San Francisco State University In calculus classes, you compute derivatives algebraically: for example, f( x) = x + x f ( x) = x x Tis tecnique requires your knowing

More information

Scale Efficiency in DEA and DEA-R with Weight Restrictions

Scale Efficiency in DEA and DEA-R with Weight Restrictions Available online at http://ijdea.rbiau.ac.ir Int. J. Data Envelopent Analyi (ISSN 2345-458X) Vol.2, No.2, Year 2014 Article ID IJDEA-00226, 5 page Reearch Article International Journal of Data Envelopent

More information