Integration of Basic Functions. Session 7 : 9/23 1

Size: px
Start display at page:

Download "Integration of Basic Functions. Session 7 : 9/23 1"

Transcription

1 Integration o Basic Fnctions Session 7 : 9/3

2 Antiderivation Integration Deinition: Taking the antiderivative, or integral, o some nction F(), reslts in the nction () i ()F() Pt simply: i yo take the integral o (), the reslting nction is (). Session 7 : 9/3

3 Relationship between dierention and integration d [ ] ( ) ( ) Dierentiation is the inverse o integration. '( ) ( ) C Integration is the inverse o dierentiation. **When the interval o integration is not speciied, called an indeinite integral. Session 7 : 9/3 3

4 Why Integrate? Common Uses:. To solve dierential eqations. To ind the area nder a crve or between crves Session 7 : 9/3 4

5 Notation: The integral o the nction ( ) 3 is written mathematically as ( ) ( ) 3 Integrand Integral symbol Dierential, i.e. With respect to Session 7 : 9/3 5

6 Eample: I ( ), then '( ) so, the integral o '( ) retrns the nction ( ) BUT Remember that the derivative o any constant is 0, so we have to accont or a possible constant when we integrate! Session 7 : 9/3 6

7 Remember Constants in Integration Integrate the ollowing nction: ( ) 4 ( ) ( 4 ) 4 C Where C is any constant Session 7 : 9/3 7

8 Basic Integration Rles. i k is a constant, k k C. i k is a constant, k ( ) k ( ) [ [ ( ) g ( )] ( ) g ( )] ( ) ( ) g ( ) g ( ) 5. n n n C, n Session 7 : 9/3 8

9 Eamples: Find the integral o: ( ) 4 g ( ) ( ) 3 4 ( ) Session 7 : 9/3 9

10 Finding Particlar Soltions Taking the integral, we are let with some nction () pls the constant C. Withot any rther inormation, we can t determine C, thereore ininite possibilities or the actal nction eist or any real vales o C. Session 7 : 9/3 0

11 Eample: '( ) F ( ) F ( ) C C C C0 so we have a general soltion, bt it isn t a particlar soltion becase we don t know what C is. C C Session 7 : 9/3

12 Particlar Soltions To ind a particlar soltion (i.e. the integral soltion at a certain vale o C), we need an initial condition An initial condition is a given vale o the integral soltion at any speciied vale o. Eample: '( ) 4 Find the general soltion (i.e. ind () withot determining C), then ind a particlar soltion (i.e. ind () and determine C) given the initial condition () 6. Session 7 : 9/3

13 Eample: Uses o Integration A model or the change in ozone concentration over time between 96 and 984 is given by: dc dt t 0 Where C is ozone concentration (ppm) and t is the elapsed time in years (96year 0). Given that in 964, the ozone concentration was 30ppm, determine the ozone concentration in 975. Session 7 : 9/3 3

14 Another Eample: The marginal cost o prodcing nits o a prodct is given by the eqation: dc Where C is the cost ($), and is the nmber o nits prodced. Given that prodcing nits o prodct costs $0, ind the cost o prodcing 300 nits. Session 7 : 9/3 4

15 The General Power Rle or Integration I is a dierentiable nction o (i.e. () is continos), then n d n d n C, n n Think reverse chain rle! Rewrite as ()d ( ( 4 ) 4 )( ) ( 4 ) d Session 7 : 9/3 5

16 Eamples: ( ) 3 ( 3 ) 3 Session 7 : 9/3 6

17 Maniplating Integrals ( 3 4 ) 4 ( ) 3 Session 7 : 9/3 7

18 Integration by Sbstittion Sometimes, terms to select or the integration process (i.e. () and d/) aren t obvios or aren t even there. In these cases, we can se integration by sbstittion to create a nction o within the eqation than can be integrated by the general power rle. Session 7 : 9/3 8

19 Eample Say we want to take the integral o the nction ( ) ( ) ( ) For this epression, there does not eist an obvios ()*d/ **Bt, we can transorm the integral to be in the orm ()*d/ Session 7 : 9/3 9

20 How? ( ) Step. Choose an obvios () (it s ine at this point that yo don t see a d/!). In this case, that is: d d Step. Take the derivative o with respect to. Write in the orm d/a. d Step 3. Solve or the epression as i the above eqation was an algebraic epression: Step 4. Sbstitte the epressions (in terms o and d) into the original integral and simpliy: ( ) d d Session 7 : 9/3 0

21 Session 7 : 9/3 Contining So now, we DO have an epression that has and d by sbstittion. This we know how to integrate sing the general power rle. d, n C n d n n Step 5. Use general power rle to integrate in terms o : D C C d Why? Becase ½*C jst creates another constant, can keep calling it C or change to keep track Step 6. Resbstitte (remember we initially determined that ). So: ( ) 3 ) ( 3

22 Integration by Sbtittion: More Eamples 3 ( ) 5 ( ) Session 7 : 9/3

23 Eponential and Logarithmic Integrals Remember: Eponentials d ( e ) e Natral Logs d (ln( )) d ( e C ) e d (ln( ) C ) d d ( e ) e ( d ) d Where is a nction o (ln( )) d Session 7 : 9/3 3

24 Integrating Eponentials e e C e d e d e C Session 7 : 9/3 4

25 Eamples: e e ( ) Original nction to integrate with respect to e C e d Rewrite, i possible, in orm e d Soltion 4e Session 7 : 9/3 5

26 Integrating Logarithmic Fnctions ln C d d ln C Where is a nction o Session 7 : 9/3 6

27 Eamples Step. Recognize i and d/ eist in epression Step. Rewrite to inclde only and d Step 3. Use rles rom previos slide to ind integral soltion Session 7 : 9/3 7

28 Rewriting Integral Eamples: e Session 7 : 9/3 8

29 Tomorrow: Integration by Parts Deinite Integrals Solving Dierential Eqations by Integrating Improper Integrals Session 7 : 9/3 9

m = Average Rate of Change (Secant Slope) Example:

m = Average Rate of Change (Secant Slope) Example: Average Rate o Change Secant Slope Deinition: The average change secant slope o a nction over a particlar interval [a, b] or [a, ]. Eample: What is the average rate o change o the nction over the interval

More information

Complex Variables. For ECON 397 Macroeconometrics Steve Cunningham

Complex Variables. For ECON 397 Macroeconometrics Steve Cunningham Comple Variables For ECON 397 Macroeconometrics Steve Cnningham Open Disks or Neighborhoods Deinition. The set o all points which satis the ineqalit

More information

Logarithmic, Exponential and Other Transcendental Functions

Logarithmic, Exponential and Other Transcendental Functions Logarithmic, Eponential an Other Transcenental Fnctions 5: The Natral Logarithmic Fnction: Differentiation The Definition First, yo mst know the real efinition of the natral logarithm: ln= t (where > 0)

More information

Differentiation of Exponential Functions

Differentiation of Exponential Functions Differentiation of Eponential Fnctions The net derivative rles that o will learn involve eponential fnctions. An eponential fnction is a fnction in the form of a constant raised to a variable power. The

More information

Section 7.4: Integration of Rational Functions by Partial Fractions

Section 7.4: Integration of Rational Functions by Partial Fractions Section 7.4: Integration of Rational Fnctions by Partial Fractions This is abot as complicated as it gets. The Method of Partial Fractions Ecept for a few very special cases, crrently we have no way to

More information

Higher Maths A1.3 Recurrence Relations - Revision

Higher Maths A1.3 Recurrence Relations - Revision Higher Maths A Recrrence Relations - Revision This revision pack covers the skills at Unit Assessment exam level or Recrrence Relations so yo can evalate yor learning o this otcome It is important that

More information

Math 116 First Midterm October 14, 2009

Math 116 First Midterm October 14, 2009 Math 116 First Midterm October 14, 9 Name: EXAM SOLUTIONS Instrctor: Section: 1. Do not open this exam ntil yo are told to do so.. This exam has 1 pages inclding this cover. There are 9 problems. Note

More information

Differentiation. The main problem of differential calculus deals with finding the slope of the tangent line at a point on a curve.

Differentiation. The main problem of differential calculus deals with finding the slope of the tangent line at a point on a curve. Dierentiation The main problem o dierential calculus deals with inding the slope o the tangent line at a point on a curve. deinition() : The slope o a curve at a point p is the slope, i it eists, o the

More information

Second-Order Wave Equation

Second-Order Wave Equation Second-Order Wave Eqation A. Salih Department of Aerospace Engineering Indian Institte of Space Science and Technology, Thirvananthapram 3 December 016 1 Introdction The classical wave eqation is a second-order

More information

Success Center Math Tips

Success Center Math Tips . Asolte Vale Eqations mer of asolte vales 3 3= o soltion Isolate the asolte vale Other side negative? Rewrite the eqation with one asolte vale on each side Write two eqations withot asolte vales: In one,

More information

3.4-Miscellaneous Equations

3.4-Miscellaneous Equations .-Miscellaneos Eqations Factoring Higher Degree Polynomials: Many higher degree polynomials can be solved by factoring. Of particlar vale is the method of factoring by groping, however all types of factoring

More information

10.2 Solving Quadratic Equations by Completing the Square

10.2 Solving Quadratic Equations by Completing the Square . Solving Qadratic Eqations b Completing the Sqare Consider the eqation ( ) We can see clearl that the soltions are However, What if the eqation was given to s in standard form, that is 6 How wold we go

More information

Bertrand s Theorem. October 8, µr 2 + V (r) 0 = dv eff dr. 3 + dv. f (r 0 )

Bertrand s Theorem. October 8, µr 2 + V (r) 0 = dv eff dr. 3 + dv. f (r 0 ) Bertrand s Theorem October 8, Circlar orbits The eective potential, V e = has a minimm or maximm at r i and only i so we mst have = dv e L µr + V r = L µ 3 + dv = L µ 3 r r = L µ 3 At this radis, there

More information

SUBJECT:ENGINEERING MATHEMATICS-I SUBJECT CODE :SMT1101 UNIT III FUNCTIONS OF SEVERAL VARIABLES. Jacobians

SUBJECT:ENGINEERING MATHEMATICS-I SUBJECT CODE :SMT1101 UNIT III FUNCTIONS OF SEVERAL VARIABLES. Jacobians SUBJECT:ENGINEERING MATHEMATICS-I SUBJECT CODE :SMT0 UNIT III FUNCTIONS OF SEVERAL VARIABLES Jacobians Changing ariable is something e come across er oten in Integration There are man reasons or changing

More information

This Topic follows on from Calculus Topics C1 - C3 to give further rules and applications of differentiation.

This Topic follows on from Calculus Topics C1 - C3 to give further rules and applications of differentiation. CALCULUS C Topic Overview C FURTHER DIFFERENTIATION This Topic follows on from Calcls Topics C - C to give frther rles applications of differentiation. Yo shold be familiar with Logarithms (Algebra Topic

More information

3. Several Random Variables

3. Several Random Variables . Several Random Variables. To Random Variables. Conditional Probabilit--Revisited. Statistical Independence.4 Correlation beteen Random Variables Standardied (or ero mean normalied) random variables.5

More information

Chapter 3. Preferences and Utility

Chapter 3. Preferences and Utility Chapter 3 Preferences and Utilit Microeconomics stdies how individals make choices; different individals make different choices n important factor in making choices is individal s tastes or preferences

More information

PhysicsAndMathsTutor.com

PhysicsAndMathsTutor.com C Integration - By sbstittion PhysicsAndMathsTtor.com. Using the sbstittion cos +, or otherwise, show that e cos + sin d e(e ) (Total marks). (a) Using the sbstittion cos, or otherwise, find the eact vale

More information

5.5 U-substitution. Solution. Z

5.5 U-substitution. Solution. Z CHAPTER 5. THE DEFINITE INTEGRAL 22 5.5 U-sbstittion Eample. (a) Fin the erivative of sin( 2 ). (b) Fin the anti-erivative cos( 2 ). Soltion. (a) We se the chain rle: sin(2 )=cos( 2 )( 2 ) 0 =cos( 2 )2

More information

Linear Strain Triangle and other types of 2D elements. By S. Ziaei Rad

Linear Strain Triangle and other types of 2D elements. By S. Ziaei Rad Linear Strain Triangle and other tpes o D elements B S. Ziaei Rad Linear Strain Triangle (LST or T6 This element is also called qadratic trianglar element. Qadratic Trianglar Element Linear Strain Triangle

More information

Unfortunately the derivative of a product is not the product of the derivatives. For example, if

Unfortunately the derivative of a product is not the product of the derivatives. For example, if Prodct Rle Unortnately te deriatie o a prodct is not te prodct o te deriaties. For eample, i Ten p So is p bt 11 1, and tey are not eal in general. Tat [ is not ] in general To compte te deriatie o a prodct

More information

BLOOM S TAXONOMY. Following Bloom s Taxonomy to Assess Students

BLOOM S TAXONOMY. Following Bloom s Taxonomy to Assess Students BLOOM S TAXONOMY Topic Following Bloom s Taonomy to Assess Stdents Smmary A handot for stdents to eplain Bloom s taonomy that is sed for item writing and test constrction to test stdents to see if they

More information

Basic properties of limits

Basic properties of limits Roberto s Notes on Dierential Calculus Chapter : Limits and continuity Section Basic properties o its What you need to know already: The basic concepts, notation and terminology related to its. What you

More information

APPENDIX B MATRIX NOTATION. The Definition of Matrix Notation is the Definition of Matrix Multiplication B.1 INTRODUCTION

APPENDIX B MATRIX NOTATION. The Definition of Matrix Notation is the Definition of Matrix Multiplication B.1 INTRODUCTION APPENDIX B MAIX NOAION he Deinition o Matrix Notation is the Deinition o Matrix Mltiplication B. INODUCION { XE "Matrix Mltiplication" }{ XE "Matrix Notation" }he se o matrix notations is not necessary

More information

LIGHTWEIGHT STRUCTURES in CIVIL ENGINEERING - CONTEMPORARY PROBLEMS

LIGHTWEIGHT STRUCTURES in CIVIL ENGINEERING - CONTEMPORARY PROBLEMS ITERATIOAL SEMIAR Organized by Polish Chapter o International Association or Shell and Spatial Strctres LIGHTWEIGHT STRUCTURES in CIVIL EGIEERIG - COTEMPORARY PROBLEMS STOCHASTIC CORROSIO EFFECTS O RELIABILITY

More information

Solving a System of Equations

Solving a System of Equations Solving a System of Eqations Objectives Understand how to solve a system of eqations with: - Gass Elimination Method - LU Decomposition Method - Gass-Seidel Method - Jacobi Method A system of linear algebraic

More information

Geometry of Span (continued) The Plane Spanned by u and v

Geometry of Span (continued) The Plane Spanned by u and v Geometric Description of Span Geometr of Span (contined) 2 Geometr of Span (contined) 2 Span {} Span {, } 2 Span {} 2 Geometr of Span (contined) 2 b + 2 The Plane Spanned b and If a plane is spanned b

More information

ECON3120/4120 Mathematics 2, spring 2009

ECON3120/4120 Mathematics 2, spring 2009 University of Oslo Department of Economics Arne Strøm ECON3/4 Mathematics, spring 9 Problem soltions for Seminar 4, 6 Febrary 9 (For practical reasons some of the soltions may inclde problem parts that

More information

Chem 4501 Introduction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics. Fall Semester Homework Problem Set Number 10 Solutions

Chem 4501 Introduction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics. Fall Semester Homework Problem Set Number 10 Solutions Chem 4501 Introdction to Thermodynamics, 3 Credits Kinetics, and Statistical Mechanics Fall Semester 2017 Homework Problem Set Nmber 10 Soltions 1. McQarrie and Simon, 10-4. Paraphrase: Apply Eler s theorem

More information

Theorem (Change of Variables Theorem):

Theorem (Change of Variables Theorem): Avance Higher Notes (Unit ) Prereqisites: Integrating (a + b) n, sin (a + b) an cos (a + b); erivatives of tan, sec, cosec, cot, e an ln ; sm/ifference rles; areas ner an between crves. Maths Applications:

More information

Math 263 Assignment #3 Solutions. 1. A function z = f(x, y) is called harmonic if it satisfies Laplace s equation:

Math 263 Assignment #3 Solutions. 1. A function z = f(x, y) is called harmonic if it satisfies Laplace s equation: Math 263 Assignment #3 Soltions 1. A fnction z f(x, ) is called harmonic if it satisfies Laplace s eqation: 2 + 2 z 2 0 Determine whether or not the following are harmonic. (a) z x 2 + 2. We se the one-variable

More information

Classify by number of ports and examine the possible structures that result. Using only one-port elements, no more than two elements can be assembled.

Classify by number of ports and examine the possible structures that result. Using only one-port elements, no more than two elements can be assembled. Jnction elements in network models. Classify by nmber of ports and examine the possible strctres that reslt. Using only one-port elements, no more than two elements can be assembled. Combining two two-ports

More information

Quadratic and Rational Inequalities

Quadratic and Rational Inequalities Chapter Qadratic Eqations and Ineqalities. Gidelines for solving word problems: (a) Write a verbal model that will describe what yo need to know. (b) Assign labels to each part of the verbal model nmbers

More information

10.4 Solving Equations in Quadratic Form, Equations Reducible to Quadratics

10.4 Solving Equations in Quadratic Form, Equations Reducible to Quadratics . Solving Eqations in Qadratic Form, Eqations Redcible to Qadratics Now that we can solve all qadratic eqations we want to solve eqations that are not eactl qadratic bt can either be made to look qadratic

More information

STEP Support Programme. STEP III Hyperbolic Functions: Solutions

STEP Support Programme. STEP III Hyperbolic Functions: Solutions STEP Spport Programme STEP III Hyperbolic Fnctions: Soltions Start by sing the sbstittion t cosh x. This gives: sinh x cosh a cosh x cosh a sinh x t sinh x dt t dt t + ln t ln t + ln cosh a ln ln cosh

More information

3. Several Random Variables

3. Several Random Variables . Several Random Variables. Two Random Variables. Conditional Probabilit--Revisited. Statistical Independence.4 Correlation between Random Variables. Densit unction o the Sum o Two Random Variables. Probabilit

More information

Differentiation of Logarithmic Functions

Differentiation of Logarithmic Functions Differentiation of Logarithmic Functions The rule for finding the derivative of a logarithmic function is given as: If y log a then dy or y. d a ( ln This rule can be proven by rewriting the logarithmic

More information

Lecture 3Section 7.3 The Logarithm Function, Part II

Lecture 3Section 7.3 The Logarithm Function, Part II Lectre 3Section 7.3 The Logarithm Fnction, Part II Jiwen He Section 7.2: Highlights 2 Properties of the Log Fnction ln = t t, ln = 0, ln e =. (ln ) = > 0. ln(y) = ln + ln y, ln(/y) = ln ln y. ln ( r) =

More information

Calculations involving a single random variable (SRV)

Calculations involving a single random variable (SRV) Calclations involving a single random variable (SRV) Example of Bearing Capacity q φ = 0 µ σ c c = 100kN/m = 50kN/m ndrained shear strength parameters What is the relationship between the Factor of Safety

More information

Shooting Method for Ordinary Differential Equations Autar Kaw

Shooting Method for Ordinary Differential Equations Autar Kaw Shooting Method or Ordinary Dierential Eqations Atar Kaw Ater reading this chapter, yo shold be able to. learn the shooting method algorithm to solve bondary vale problems, and. apply shooting method to

More information

Methods for Advanced Mathematics (C3) FRIDAY 11 JANUARY 2008

Methods for Advanced Mathematics (C3) FRIDAY 11 JANUARY 2008 ADVANCED GCE 4753/ MATHEMATICS (MEI) Methods for Advanced Mathematics (C3) FRIDAY JANUARY 8 Additional materials: Answer Booklet (8 pages) Graph paper MEI Eamination Formlae and Tables (MF) Morning Time:

More information

A New Approach to Direct Sequential Simulation that Accounts for the Proportional Effect: Direct Lognormal Simulation

A New Approach to Direct Sequential Simulation that Accounts for the Proportional Effect: Direct Lognormal Simulation A ew Approach to Direct eqential imlation that Acconts for the Proportional ffect: Direct ognormal imlation John Manchk, Oy eangthong and Clayton Detsch Department of Civil & nvironmental ngineering University

More information

Lesson 81: The Cross Product of Vectors

Lesson 81: The Cross Product of Vectors Lesson 8: The Cross Prodct of Vectors IBHL - SANTOWSKI In this lesson yo will learn how to find the cross prodct of two ectors how to find an orthogonal ector to a plane defined by two ectors how to find

More information

Physics 5153 Classical Mechanics. Solution by Quadrature-1

Physics 5153 Classical Mechanics. Solution by Quadrature-1 October 14, 003 11:47:49 1 Introduction Physics 5153 Classical Mechanics Solution by Quadrature In the previous lectures, we have reduced the number o eective degrees o reedom that are needed to solve

More information

EXERCISES WAVE EQUATION. In Problems 1 and 2 solve the heat equation (1) subject to the given conditions. Assume a rod of length L.

EXERCISES WAVE EQUATION. In Problems 1 and 2 solve the heat equation (1) subject to the given conditions. Assume a rod of length L. .4 WAVE EQUATION 445 EXERCISES.3 In Problems and solve the heat eqation () sbject to the given conditions. Assme a rod of length.. (, t), (, t) (, ),, > >. (, t), (, t) (, ) ( ) 3. Find the temperatre

More information

Chapter 9 Flow over Immersed Bodies

Chapter 9 Flow over Immersed Bodies 57:00 Mechanics o Flids and Transport Processes Chapter 9 Proessor Fred Stern Fall 01 1 Chapter 9 Flow over Immersed Bodies Flid lows are broadly categorized: 1. Internal lows sch as dcts/pipes, trbomachinery,

More information

Technical Note. ODiSI-B Sensor Strain Gage Factor Uncertainty

Technical Note. ODiSI-B Sensor Strain Gage Factor Uncertainty Technical Note EN-FY160 Revision November 30, 016 ODiSI-B Sensor Strain Gage Factor Uncertainty Abstract Lna has pdated or strain sensor calibration tool to spport NIST-traceable measrements, to compte

More information

Sec 3.1. lim and lim e 0. Exponential Functions. f x 9, write the equation of the graph that results from: A. Limit Rules

Sec 3.1. lim and lim e 0. Exponential Functions. f x 9, write the equation of the graph that results from: A. Limit Rules Sec 3. Eponential Functions A. Limit Rules. r lim a a r. I a, then lim a and lim a 0 3. I 0 a, then lim a 0 and lim a 4. lim e 0 5. e lim and lim e 0 Eamples:. Starting with the graph o a.) Shiting 9 units

More information

Essentials of optimal control theory in ECON 4140

Essentials of optimal control theory in ECON 4140 Essentials of optimal control theory in ECON 4140 Things yo need to know (and a detail yo need not care abot). A few words abot dynamic optimization in general. Dynamic optimization can be thoght of as

More information

RATIONAL FUNCTIONS. Finding Asymptotes..347 The Domain Finding Intercepts Graphing Rational Functions

RATIONAL FUNCTIONS. Finding Asymptotes..347 The Domain Finding Intercepts Graphing Rational Functions RATIONAL FUNCTIONS Finding Asymptotes..347 The Domain....350 Finding Intercepts.....35 Graphing Rational Functions... 35 345 Objectives The ollowing is a list o objectives or this section o the workbook.

More information

Chapter 6 Momentum Transfer in an External Laminar Boundary Layer

Chapter 6 Momentum Transfer in an External Laminar Boundary Layer 6. Similarit Soltions Chapter 6 Momentm Transfer in an Eternal Laminar Bondar Laer Consider a laminar incompressible bondar laer with constant properties. Assme the flow is stead and two-dimensional aligned

More information

Section 3.4: Concavity and the second Derivative Test. Find any points of inflection of the graph of a function.

Section 3.4: Concavity and the second Derivative Test. Find any points of inflection of the graph of a function. Unit 3: Applications o Dierentiation Section 3.4: Concavity and the second Derivative Test Determine intervals on which a unction is concave upward or concave downward. Find any points o inlection o the

More information

Exponential, Logarithmic and Inverse Functions

Exponential, Logarithmic and Inverse Functions Chapter Review Sec.1 and. Eponential, Logarithmic and Inverse Functions I. Review o Inverrse I Functti ions A. Identiying One-to-One Functions is one-to-one i every element in the range corresponds to

More information

Solutions to Math 152 Review Problems for Exam 1

Solutions to Math 152 Review Problems for Exam 1 Soltions to Math 5 Review Problems for Eam () If A() is the area of the rectangle formed when the solid is sliced at perpendiclar to the -ais, then A() = ( ), becase the height of the rectangle is and

More information

Linear System Theory (Fall 2011): Homework 1. Solutions

Linear System Theory (Fall 2011): Homework 1. Solutions Linear System Theory (Fall 20): Homework Soltions De Sep. 29, 20 Exercise (C.T. Chen: Ex.3-8). Consider a linear system with inpt and otpt y. Three experiments are performed on this system sing the inpts

More information

Extreme Values of Functions

Extreme Values of Functions Extreme Values o Functions When we are using mathematics to model the physical world in which we live, we oten express observed physical quantities in terms o variables. Then, unctions are used to describe

More information

0,0 B 5,0 C 0, 4 3,5. y x. Recitation Worksheet 1A. 1. Plot these points in the xy plane: A

0,0 B 5,0 C 0, 4 3,5. y x. Recitation Worksheet 1A. 1. Plot these points in the xy plane: A Math 13 Recitation Worksheet 1A 1 Plot these points in the y plane: A 0,0 B 5,0 C 0, 4 D 3,5 Without using a calculator, sketch a graph o each o these in the y plane: A y B 3 Consider the unction a Evaluate

More information

Figure 1 Probability density function of Wedge copula for c = (best fit to Nominal skew of DRAM case study).

Figure 1 Probability density function of Wedge copula for c = (best fit to Nominal skew of DRAM case study). Wedge Copla This docment explains the constrction and properties o a particlar geometrical copla sed to it dependency data rom the edram case stdy done at Portland State University. The probability density

More information

Partial Differential Equations with Applications

Partial Differential Equations with Applications Universit of Leeds MATH 33 Partial Differential Eqations with Applications Eamples to spplement Chapter on First Order PDEs Eample (Simple linear eqation, k + = 0, (, 0) = ϕ(), k a constant.) The characteristic

More information

Quadratic forms and a some matrix computations

Quadratic forms and a some matrix computations Linear Algebra or Wireless Conications Lectre: 8 Qadratic ors and a soe atri coptations Ove Edors Departent o Electrical and Inoration echnology Lnd University it Stationary points One diension ( d d =

More information

Conditions for Approaching the Origin without Intersecting the x-axis in the Liénard Plane

Conditions for Approaching the Origin without Intersecting the x-axis in the Liénard Plane Filomat 3:2 (27), 376 377 https://doi.org/.2298/fil7276a Pblished by Faclty of Sciences and Mathematics, University of Niš, Serbia Available at: http://www.pmf.ni.ac.rs/filomat Conditions for Approaching

More information

4 Exact laminar boundary layer solutions

4 Exact laminar boundary layer solutions 4 Eact laminar bondary layer soltions 4.1 Bondary layer on a flat plate (Blasis 1908 In Sec. 3, we derived the bondary layer eqations for 2D incompressible flow of constant viscosity past a weakly crved

More information

ON THE SHAPES OF BILATERAL GAMMA DENSITIES

ON THE SHAPES OF BILATERAL GAMMA DENSITIES ON THE SHAPES OF BILATERAL GAMMA DENSITIES UWE KÜCHLER, STEFAN TAPPE Abstract. We investigate the for parameter family of bilateral Gamma distribtions. The goal of this paper is to provide a thorogh treatment

More information

Curve Sketching. The process of curve sketching can be performed in the following steps:

Curve Sketching. The process of curve sketching can be performed in the following steps: Curve Sketching So ar you have learned how to ind st and nd derivatives o unctions and use these derivatives to determine where a unction is:. Increasing/decreasing. Relative extrema 3. Concavity 4. Points

More information

Change of Variables. (f T) JT. f = U

Change of Variables. (f T) JT. f = U Change of Variables 4-5-8 The change of ariables formla for mltiple integrals is like -sbstittion for single-ariable integrals. I ll gie the general change of ariables formla first, and consider specific

More information

The Linear Quadratic Regulator

The Linear Quadratic Regulator 10 The Linear Qadratic Reglator 10.1 Problem formlation This chapter concerns optimal control of dynamical systems. Most of this development concerns linear models with a particlarly simple notion of optimality.

More information

Formal Methods for Deriving Element Equations

Formal Methods for Deriving Element Equations Formal Methods for Deriving Element Eqations And the importance of Shape Fnctions Formal Methods In previos lectres we obtained a bar element s stiffness eqations sing the Direct Method to obtain eact

More information

The Oscillatory Stable Regime of Nonlinear Systems, with two time constants

The Oscillatory Stable Regime of Nonlinear Systems, with two time constants 6th WSES International Conference on CIRCUITS SYSTEMS ELECTRONICSCONTROL & SIGNL PROCESSING Cairo Egpt Dec 9-3 7 5 The Oscillator Stable Regime of Nonlinear Sstems with two time constants NUŢU VSILE *

More information

This is only a list of questions use a separate sheet to work out the problems. 1. (1.2 and 1.4) Use the given graph to answer each question.

This is only a list of questions use a separate sheet to work out the problems. 1. (1.2 and 1.4) Use the given graph to answer each question. Mth Calculus Practice Eam Questions NOTE: These questions should not be taken as a complete list o possible problems. The are merel intended to be eamples o the diicult level o the regular eam questions.

More information

Functions. Essential Question What are some of the characteristics of the graph of a logarithmic function?

Functions. Essential Question What are some of the characteristics of the graph of a logarithmic function? 5. Logarithms and Logarithmic Functions Essential Question What are some o the characteristics o the graph o a logarithmic unction? Ever eponential unction o the orm () = b, where b is a positive real

More information

The Cross Product of Two Vectors in Space DEFINITION. Cross Product. u * v = s ƒ u ƒƒv ƒ sin ud n

The Cross Product of Two Vectors in Space DEFINITION. Cross Product. u * v = s ƒ u ƒƒv ƒ sin ud n 12.4 The Cross Prodct 873 12.4 The Cross Prodct In stdying lines in the plane, when we needed to describe how a line was tilting, we sed the notions of slope and angle of inclination. In space, we want

More information

11.6 Directional Derivative & The Gradient Vector. Working Definitions

11.6 Directional Derivative & The Gradient Vector. Working Definitions 1 Ma 016 1 Kidogchi Kenneth The directional derivative o at 0 0 ) in the direction o the nit vector is the scalar nction deined b: where q is angle between the two vectors placed tail-to-tail and 0 < q

More information

INTRODUCTORY MATHEMATICAL ANALYSIS

INTRODUCTORY MATHEMATICAL ANALYSIS INTRODUCTORY MATHEMATICAL ANALYSIS For Business, Economics, and the Lie and Social Sciences Chapter 11 Dierentiation 011 Pearson Education, Inc. Chapter 11: Dierentiation Chapter Objectives To compute

More information

Simplified Identification Scheme for Structures on a Flexible Base

Simplified Identification Scheme for Structures on a Flexible Base Simplified Identification Scheme for Strctres on a Flexible Base L.M. Star California State University, Long Beach G. Mylonais University of Patras, Greece J.P. Stewart University of California, Los Angeles

More information

Lecture Notes On THEORY OF COMPUTATION MODULE - 2 UNIT - 2

Lecture Notes On THEORY OF COMPUTATION MODULE - 2 UNIT - 2 BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ODISHA Lectre Notes On THEORY OF COMPUTATION MODULE - 2 UNIT - 2 Prepared by, Dr. Sbhend Kmar Rath, BPUT, Odisha. Tring Machine- Miscellany UNIT 2 TURING MACHINE

More information

Vectors in Rn un. This definition of norm is an extension of the Pythagorean Theorem. Consider the vector u = (5, 8) in R 2

Vectors in Rn un. This definition of norm is an extension of the Pythagorean Theorem. Consider the vector u = (5, 8) in R 2 MATH 307 Vectors in Rn Dr. Neal, WKU Matrices of dimension 1 n can be thoght of as coordinates, or ectors, in n- dimensional space R n. We can perform special calclations on these ectors. In particlar,

More information

y,z the subscript y, z indicating that the variables y and z are kept constant. The second partial differential with respect to x is written x 2 y,z

y,z the subscript y, z indicating that the variables y and z are kept constant. The second partial differential with respect to x is written x 2 y,z 8 Partial dierentials I a unction depends on more than one variable, its rate o change with respect to one o the variables can be determined keeping the others ied The dierential is then a partial dierential

More information

Mat 241 Homework Set 3 Due Professor David Schultz

Mat 241 Homework Set 3 Due Professor David Schultz Mat 4 Homework Set De Professor David Schltz Directions: Show all algebraic steps neatly and concisely sing proper mathematical symbolism. When graphs and technology are to be implemented, do so appropriately.

More information

Lecture: Corporate Income Tax

Lecture: Corporate Income Tax Lectre: Corporate Income Tax Ltz Krschwitz & Andreas Löffler Disconted Cash Flow, Section 2.1, Otline 2.1 Unlevered firms Similar companies Notation 2.1.1 Valation eqation 2.1.2 Weak atoregressive cash

More information

2. Find the coordinates of the point where the line tangent to the parabola 2

2. Find the coordinates of the point where the line tangent to the parabola 2 00. lim 3 3 3 = (B) (C) 0 (D) (E). Find the coordinates of the point where the line tangent to the parabola y = 4 at = 4 intersects the ais of symmetry of the parabola. 3. If f () = 7 and f () = 3, then

More information

Microscopic Properties of Gases

Microscopic Properties of Gases icroscopic Properties of Gases So far we he seen the gas laws. These came from observations. In this section we want to look at a theory that explains the gas laws: The kinetic theory of gases or The kinetic

More information

Department of Industrial Engineering Statistical Quality Control presented by Dr. Eng. Abed Schokry

Department of Industrial Engineering Statistical Quality Control presented by Dr. Eng. Abed Schokry Department of Indstrial Engineering Statistical Qality Control presented by Dr. Eng. Abed Schokry Department of Indstrial Engineering Statistical Qality Control C and U Chart presented by Dr. Eng. Abed

More information

CHARACTERIZATIONS OF EXPONENTIAL DISTRIBUTION VIA CONDITIONAL EXPECTATIONS OF RECORD VALUES. George P. Yanev

CHARACTERIZATIONS OF EXPONENTIAL DISTRIBUTION VIA CONDITIONAL EXPECTATIONS OF RECORD VALUES. George P. Yanev Pliska Std. Math. Blgar. 2 (211), 233 242 STUDIA MATHEMATICA BULGARICA CHARACTERIZATIONS OF EXPONENTIAL DISTRIBUTION VIA CONDITIONAL EXPECTATIONS OF RECORD VALUES George P. Yanev We prove that the exponential

More information

EE2 Mathematics : Functions of Multiple Variables

EE2 Mathematics : Functions of Multiple Variables EE2 Mathematics : Fnctions of Mltiple Variables http://www2.imperial.ac.k/ nsjones These notes are not identical word-for-word with m lectres which will be gien on the blackboard. Some of these notes ma

More information

Lecture Notes: Finite Element Analysis, J.E. Akin, Rice University

Lecture Notes: Finite Element Analysis, J.E. Akin, Rice University 9. TRUSS ANALYSIS... 1 9.1 PLANAR TRUSS... 1 9. SPACE TRUSS... 11 9.3 SUMMARY... 1 9.4 EXERCISES... 15 9. Trss analysis 9.1 Planar trss: The differential eqation for the eqilibrim of an elastic bar (above)

More information

Robust Shortest Path Planning and Semicontractive Dynamic Programming

Robust Shortest Path Planning and Semicontractive Dynamic Programming ebrary 4 (Revised Agst 4, ne 6 Report LIDS - 95 Robst Shortest Path Planning Semicontractive Dynamic Programg Dimitri P. Bertseas Abstract In this paper we consider shortest path in a directed graph where

More information

FRTN10 Exercise 12. Synthesis by Convex Optimization

FRTN10 Exercise 12. Synthesis by Convex Optimization FRTN Exercise 2. 2. We want to design a controller C for the stable SISO process P as shown in Figre 2. sing the Yola parametrization and convex optimization. To do this, the control loop mst first be

More information

Objectives. By the time the student is finished with this section of the workbook, he/she should be able

Objectives. By the time the student is finished with this section of the workbook, he/she should be able FUNCTIONS Quadratic Functions......8 Absolute Value Functions.....48 Translations o Functions..57 Radical Functions...61 Eponential Functions...7 Logarithmic Functions......8 Cubic Functions......91 Piece-Wise

More information

Curves - Foundation of Free-form Surfaces

Curves - Foundation of Free-form Surfaces Crves - Fondation of Free-form Srfaces Why Not Simply Use a Point Matrix to Represent a Crve? Storage isse and limited resoltion Comptation and transformation Difficlties in calclating the intersections

More information

Subcritical bifurcation to innitely many rotating waves. Arnd Scheel. Freie Universitat Berlin. Arnimallee Berlin, Germany

Subcritical bifurcation to innitely many rotating waves. Arnd Scheel. Freie Universitat Berlin. Arnimallee Berlin, Germany Sbcritical bifrcation to innitely many rotating waves Arnd Scheel Institt fr Mathematik I Freie Universitat Berlin Arnimallee 2-6 14195 Berlin, Germany 1 Abstract We consider the eqation 00 + 1 r 0 k2

More information

Bayes and Naïve Bayes Classifiers CS434

Bayes and Naïve Bayes Classifiers CS434 Bayes and Naïve Bayes Classifiers CS434 In this lectre 1. Review some basic probability concepts 2. Introdce a sefl probabilistic rle - Bayes rle 3. Introdce the learning algorithm based on Bayes rle (ths

More information

Chapter 2 Difficulties associated with corners

Chapter 2 Difficulties associated with corners Chapter Difficlties associated with corners This chapter is aimed at resolving the problems revealed in Chapter, which are cased b corners and/or discontinos bondar conditions. The first section introdces

More information

APPLICATIONS OF DIFFERENTIATION

APPLICATIONS OF DIFFERENTIATION 4 APPLICATIONS OF DIFFERENTIATION APPLICATIONS OF DIFFERENTIATION 4.4 Indeterminate Forms and L Hospital s Rule In this section, we will learn: How to evaluate functions whose values cannot be found at

More information

Place value and fractions. Explanation and worked examples We read this number as two hundred and fifty-six point nine one.

Place value and fractions. Explanation and worked examples We read this number as two hundred and fifty-six point nine one. 3 3 Place vale and ractions Exlanation and worked examles Level Yo shold know and nderstand which digit o a nmer shows the nmer o: ten thosands 0 000 thosands 000 hndreds 00 tens 0 nits As well as the

More information

1/100 Range: 1/10 1/ 2. 1) Constant: choose a value for the constant that can be graphed on the coordinate grid below.

1/100 Range: 1/10 1/ 2. 1) Constant: choose a value for the constant that can be graphed on the coordinate grid below. Name 1) Constant: choose a value or the constant that can be graphed on the coordinate grid below a y Toolkit Functions Lab Worksheet thru inverse trig ) Identity: y ) Reciprocal: 1 ( ) y / 1/ 1/1 1/ 1

More information

Setting The K Value And Polarization Mode Of The Delta Undulator

Setting The K Value And Polarization Mode Of The Delta Undulator LCLS-TN-4- Setting The Vale And Polarization Mode Of The Delta Undlator Zachary Wolf, Heinz-Dieter Nhn SLAC September 4, 04 Abstract This note provides the details for setting the longitdinal positions

More information

Formules relatives aux probabilités qui dépendent de très grands nombers

Formules relatives aux probabilités qui dépendent de très grands nombers Formles relatives ax probabilités qi dépendent de très grands nombers M. Poisson Comptes rends II (836) pp. 603-63 In the most important applications of the theory of probabilities, the chances of events

More information

Reduction of over-determined systems of differential equations

Reduction of over-determined systems of differential equations Redction of oer-determined systems of differential eqations Maim Zaytse 1) 1, ) and Vyachesla Akkerman 1) Nclear Safety Institte, Rssian Academy of Sciences, Moscow, 115191 Rssia ) Department of Mechanical

More information

Gradient Projection Anti-windup Scheme on Constrained Planar LTI Systems. Justin Teo and Jonathan P. How

Gradient Projection Anti-windup Scheme on Constrained Planar LTI Systems. Justin Teo and Jonathan P. How 1 Gradient Projection Anti-windp Scheme on Constrained Planar LTI Systems Jstin Teo and Jonathan P. How Technical Report ACL1 1 Aerospace Controls Laboratory Department of Aeronatics and Astronatics Massachsetts

More information

Math Review and Lessons in Calculus

Math Review and Lessons in Calculus Math Review and Lessons in Calculus Agenda Rules o Eponents Functions Inverses Limits Calculus Rules o Eponents 0 Zero Eponent Rule a * b ab Product Rule * 3 5 a / b a-b Quotient Rule 5 / 3 -a / a Negative

More information