Generalized Inverses: How to Invert a Non-Invertible Matrix
|
|
- Ashlyn McCormick
- 7 years ago
- Views:
Transcription
1 Generlized Inverses: How to Invert Non-Invertible Mtrix S. Swyer September 7, 2006 rev August 6, Introduction nd Definition. Let A be generl m n mtrix. Then nturl question is when we cn solve Ax y for x R m, given y R n. If A is squre mtrix m n nd A hs n inverse, then. holds if nd only if x A y. This gives complete nswer if A is invertible. However, A my be m n with m n, or A my be squre mtrix tht is not invertible. If A is not invertible, then eqution. my hve no solutions tht is, y my be not be in the rnge of A, nd if there re solutions, then there my be mny different solutions. 2 0 For exmple, ssume A. Then A, so tht 6 0 A is not invertible. It would be useful to hve chrcteriztion of those y R 2 for which it is possible to find solution of Ax y, nd, if Ax y is solution, to find ll possible solutions. It is esy to nswer these questions directly for 2 2 mtrix, but not if A were 8 or 0 0. A solution of these questions cn be found in generl from the notion of generlized inverse of mtrix: Definition. If A is n m n mtrix, then G is generlized inverse of A if G is n n m mtrix with AGA A.2 If A hs n inverse in the usul sense, tht is if A is n n nd hs two-sided inverse A, then while by.2 A AGAA A A G AA G A AA A AA A Thus, if A exists in the usul sense, then G A. This justifies the term generlized inverse. We will see lter tht ny m n mtrix A hs t lest one generlized inverse G. However, unless A is n n nd A is invertible,
2 Generlized Inverses there re mny different generlized inverses G, so tht G is not unique. Generlized inverses re unique is you impose more conditions on G; see Section below. One consequence of.2 is tht AGAGAG nd GAGAGA. In generl, squre mtrix P tht stisfies P 2 P is clled projection mtrix. Thus both AG nd GA re projection mtrices. Since A is m n nd G is n m, AG is n m m projection mtrix nd GA is n n. In generl if P is projection mtrix, then P P 2 implies P y P P y nd P z z for for ll z P y in the rnge of P. Tht is, if P is n n, P moves ny x R n into V {P x : x R n } the rnge of P nd then keeps it t the sme plce. If x R n, then y P x nd z x P x I P x stisfies x y + z, P y y, nd P z P x P x P x P 2 x 0. Since then P x P y + z y, we cn sy tht P projects R n onto its rnge V long the spce W {x : P x 0}. The two projections AG nd GA both pper in the next result, which shows how generlized inverses cn be used to solve mtrix equtions. Theorem.. Let A by n m n mtrix nd ssume tht G is generlized inverse of A tht is, AGA A. Then, for ny fixed y R m, i the eqution Ax y, x R n. hs solution x R n if nd only if AGy y tht is, if nd only if y is in the rnge of the projection AG. ii If Ax y hs ny solutions, then x is solution of Ax y if nd only if x Gy + I GAz for some z R n.4 Remrk. If we wnt prticulr solution of Ax y for y in the rnge of A, we cn tke x Gy. Proof of Theorem.. All of the prts of the theorem re esy to prove, but some involve somewht unintuitive mnipultions of mtrices. Proof of prt i: If y is in the rnge of the projection AG, tht is if AGy y, then AGy y nd x Gy is solution of Ax y. Conversely, if Ax y, then GAx Gy nd AGAx AGy AGy, while AGA A implies AGAx Ax y. Thus AGy y. Thus, if Ax y hs ny solutions for given y R m, then x Gy is prticulr solution. Proof of prt ii: This hs two prts: First, if AGy y, then ll of the vectors in.4 re solutions of Ax y. Second, tht.4 contins ll possible solutions of Ax y.
3 Generlized Inverses If AGy y nd x Gy + I GAz, then Ax AGy + AI GAz y + A AGAz y, so tht ny x R n tht stisfies.4 with AGy y is solution of Ax y. Conversely, if Ax y, let z x. Then the right-hnd side of.4 is Gy +I GAx Gy +x GAx Gy +x Gy x, so tht ny solution x of Ax y is given by.4 with z x. 0 Exmple. Let A s before. Set G. Then AGA A 6 so tht G is generlized inverse of A. The two projections ppering in Theorem. re 0 AG nd GA 0 In this cse A x y 6 x x + 2y y x + 6y Thus Ax y hs solution x only if y c AG x y 0 0 x y x x x + 2y x. On the other hnd, so tht the rnge of the projection AG is exctly the set of vectors { c The theorem then sys tht if y c }., then the set of solutions of Ax y is exctly z x Gc + I GA z z c + 0 z z 2 c + c + z 0 2 z 2.5 It is esy to check tht Ax y c for ll x in.5, nd, with some extr work, tht these re ll solutions.
4 Generlized Inverses The ABCD-Theorem nd Generlized Inverses of Arbitrry Mtrices. Let A be n rbitrry m n mtrix; tht is, with n columns nd m rows. Then we cn write 2... n n A v v 2... v n m m2... mn w w w m where v i re the columns of A nd w j re the rows. In generl, the column rnk of A cll it r c is the dimension of the vector spce in R m tht is spnned by the columns {v i } of A, nd the row rnk of A cll it r r is the dimension of the vector spce in R n tht is spnned by the rows {w j } of A. Tht is, r c is the lrgest number of linerly-independent columns v i in R m, nd r r is the the lrgest number of linerly-independent rows w j in R n. Then r c m, since the lrgest number of linerly independent vectors in R m is m, nd r c n since there re only n columns to begin with. Thus r c min{m, n}. By the sme rguments, r r min{m, n}. It cn be shown tht r c r r for ny m n mtrix, so tht the row rnk nd the column rnk of n rbitrry mtrix A re the sme. The common vlue r r c r r min{m, n} is clled the rnk of A. Let A be n m n mtrix with rnka r min{m, n} s bove. Then, one cn show tht, fter suitble rerrngement of rows nd columns, A cn be written in prtitioned form s A 2. c d where is r r nd invertible, b is r n r, c is m r r, nd d is m r n r. In fct, we cn prove the following representtion theorem for generl mtrices: Theorem 2.. Let A is n m n mtrix with rnk r rnka. Then the rows nd columns cn be permuted so tht it cn be written in the prtitioned form 2. where is r r nd invertible. In tht cse d c b, so tht A c c.2 b Note tht, b, c, d in 2. nd 2.2 re mtrices, not numbers. Some of the entries b, c, d in 2. my be empty, in which cse they do not pper, for exmple if m n nd A is invertible.
5 Generlized Inverses Remrks. If A is 2 2 mtrix of numbers with > 0 but c d r rnka, then deta d bc 0. This implies d bc/. We cnnot write bc/ for mtrices, but 2.2 with d b c is the pproprite generliztion for mtrices. The mtrix d c b is lwys defined nd is m r n r, since c is m r r, is r r, nd b is r n r. Exmple. Let A xy be the outer product of vectors x R m nd y R n, so tht A is m n. Assume x 0 nd y 0. Then rnka since every row of A is multiple of y nd every column of A is multiple of x. In this cse, we cn write A xy y x y x y 2... y n x 2... x 2y 2... x 2 y n x m x m y 2... x m y n This is in the form 2.2 where b x y 2... y n is n row vector, c y x 2... x m is n m column vector, nd d b c y x 2... x m x y x y 2... y n x 2... x m y 2... y n is the outer product of n m -dimensionl vector nd n n - dimensionl vector. Remrk. A Note tht 2.2 cn lso be written Ir c c I c r b This cn be viewed s generliztion of the representtion A uv for n outer product of two vectors u, v. Proof of Theorem 2.. If the first r rows of A re linerly independent nd rnka rnk r in 2., then the lst m r rows of A re liner combintions of the first r rows. This mens tht we cn write the lst m r rows of A s c d i r T ij j for i m r j
6 Generlized Inverses where T ij i m r, j r re numbers. In terms of mtrices, c d T T T b 2. where T is m r r. The reltion 2. implies c T nd hence T c. This implies T b c b d in 2., which completes the proof of Theorem 2.. Theorem 2.2. Let A c d c c b 2.4 be n m n mtrix with r rnka where is r r nd invertible, s in Theorem 2.. Let 0 G 2.5 where the 0 s in 2.5 represent mtrices of zeroes of dimension sufficient to mke G n n m mtrix. Then G is generlized inverse of A. Proof. By 2.4 nd 2.5 c 0 d c Ir 0 c 0 c d d c c b where I r is the r r unit mtrix. This implies AGA A since d c b by 2.4, so tht G is generlized inverse of A. The two projections in this cse re AG Ir 0 c 0 nd GA Theorem. then sys tht Ax y y 2 R m r if nd only if AGy Ir 0 y c 0 y 2 y y 2 Ir b y c y cn be solved for y R r, y y 2
7 Generlized Inverses Tht is, if nd only if y 2 c y. In tht cse, the generl solution of Ax y for x R n is x x Gy + I x m GAz 2 0 y 0 + b z y 2 0 I m r z 2 y + bz 2 0 for rbitrry z 2 R m r. Remrk. This shows tht ny m n mtrix A hs t lest one generlized inverse G of the form 2.5. Since often mny different linerly-independent sets of r rows cn be permuted to the upper r rows nd mny different linerly-independent sets of r columns cn be permuted into the first r column positions, mtrix A with rnka r < n cn hve mny different generlized inverses of this form.. The Penrose Inverse. In generl, n m n mtrix A hs mny different generlized inverses unless m n nd A is invertible. It is possible, however, to dd conditions to the definition of generlized inverse so tht there is lwys unique generlized inverse under the dditionl conditions. Definition. G is clled Penrose inverse of the m n mtrix A if G is n n m mtrix tht stisfies the four conditions i AGA A ii GAG G iii AG AG is n orthogonl projection in R m iv GA GA is n orthogonl projection in R n Condition ii sys tht A is generlized inverse of G, in ddition to G being generlized inverse of A. The fct thn n rbitrry m n mtrix A hs unique n m Penrose inverse follows from the Singulr Vlue Decomposition theorem in mtrix lgebr. Some generlized inverses tht re nturl to use in prctice re Penrose inverses nd some re not. The next section gives n exmple of Penrose inverse. 4. Fitted Vlues in Sttistics. Let X be n n r mtrix with r < n nd rnkx r. Then X X is invertible. If observed vlues Y R n cn be exctly fit by the prmeters β R r, then z 2 Y Xβ, Y R n, β R r 4.
8 Generlized Inverses The mtrix X cnnot be invertible, since r < n. However, suppose tht we wnt generl procedure to choose n rbitrry β in terms of Y, in the hopes tht lter we cn find justifiction for this procedure other thn it gives definite nswer. In tht cse, we cn consider generlized inverse of X. Specificlly, G will be generlized inverse of X if G is r n nd XGX X Since X X is invertible, n obvious choice is G X X X 4.2 since then XGX XX X X X X. The two projections XG nd GX re GX X X X X I r nd XG XX X X H 4. Note tht both projections re symmetric: Tht is, I r I r nd H H. In ddition GXG X X X XX X X X X X G Tht is, G is the unique Penrose inverse of the n r mtrix X. Theorem. now sys tht Y Xβ cn be solved exctly if nd only if XGY HY Y ; tht is, if nd only if Y is in the rnge of the n n projection H. Moreover, if HY Y, then every solution of Xβ Y is of the form β GY X X X Y + I r GXz, z R r X X X Y 4.4 since GX I r by 4.. In other words, if Y Xβ for some vector β, then the only solution β of Xβ Y for given Y is given by 4.4. Indeed, it follows directly from 4. tht X must be one-one: Tht is, if Xβ Xβ 2, then GXβ GXβ 2 β β 2. There is etter motivtion for the solution β GY for G in 4.2 thn rbitrriness or orneriness. Suppose tht we view Y s Xβ tht re observed with errors. Tht is, s Y Xβ + e 4.5
9 Generlized Inverses where e {e i } re independent errors. Then we cn consider the vlue of β tht minimizes the sum of errors min β n 2 n Yi Xβ i Yi X β 2 i 4.6 i i If we set This implies n 2 n Yi Xβ i Y i β j β i j i n r 2 Y i X i β X ij 0 i r 2 X i β r n X ij X i β i n X ij Y i, i j r which cn be written in more compct form s X Xβ X Y 4.7 Since we re ssuming tht X X is invertible, 4.7 implies β X X X Y GY for G in 4.2. Tht is, the lest-squres solution of 4.6 for β is given by β β GY, where G is the Penrose inverse of the n r mtrix X.
and thus, they are similar. If k = 3 then the Jordan form of both matrices is
Homework ssignment 11 Section 7. pp. 249-25 Exercise 1. Let N 1 nd N 2 be nilpotent mtrices over the field F. Prove tht N 1 nd N 2 re similr if nd only if they hve the sme miniml polynomil. Solution: If
More information4.11 Inner Product Spaces
314 CHAPTER 4 Vector Spces 9. A mtrix of the form 0 0 b c 0 d 0 0 e 0 f g 0 h 0 cnnot be invertible. 10. A mtrix of the form bc d e f ghi such tht e bd = 0 cnnot be invertible. 4.11 Inner Product Spces
More informationExample 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers.
2 Rtionl Numbers Integers such s 5 were importnt when solving the eqution x+5 = 0. In similr wy, frctions re importnt for solving equtions like 2x = 1. Wht bout equtions like 2x + 1 = 0? Equtions of this
More informationLINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES
LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES DAVID WEBB CONTENTS Liner trnsformtions 2 The representing mtrix of liner trnsformtion 3 3 An ppliction: reflections in the plne 6 4 The lgebr of
More informationMATH 150 HOMEWORK 4 SOLUTIONS
MATH 150 HOMEWORK 4 SOLUTIONS Section 1.8 Show tht the product of two of the numbers 65 1000 8 2001 + 3 177, 79 1212 9 2399 + 2 2001, nd 24 4493 5 8192 + 7 1777 is nonnegtive. Is your proof constructive
More informationMODULE 3. 0, y = 0 for all y
Topics: Inner products MOULE 3 The inner product of two vectors: The inner product of two vectors x, y V, denoted by x, y is (in generl) complex vlued function which hs the following four properties: i)
More informationVectors 2. 1. Recap of vectors
Vectors 2. Recp of vectors Vectors re directed line segments - they cn be represented in component form or by direction nd mgnitude. We cn use trigonometry nd Pythgors theorem to switch between the forms
More informationPolynomial Functions. Polynomial functions in one variable can be written in expanded form as ( )
Polynomil Functions Polynomil functions in one vrible cn be written in expnded form s n n 1 n 2 2 f x = x + x + x + + x + x+ n n 1 n 2 2 1 0 Exmples of polynomils in expnded form re nd 3 8 7 4 = 5 4 +
More informationGraphs on Logarithmic and Semilogarithmic Paper
0CH_PHClter_TMSETE_ 3//00 :3 PM Pge Grphs on Logrithmic nd Semilogrithmic Pper OBJECTIVES When ou hve completed this chpter, ou should be ble to: Mke grphs on logrithmic nd semilogrithmic pper. Grph empiricl
More informationLecture 5. Inner Product
Lecture 5 Inner Product Let us strt with the following problem. Given point P R nd line L R, how cn we find the point on the line closest to P? Answer: Drw line segment from P meeting the line in right
More informationPHY 140A: Solid State Physics. Solution to Homework #2
PHY 140A: Solid Stte Physics Solution to Homework # TA: Xun Ji 1 October 14, 006 1 Emil: jixun@physics.ucl.edu Problem #1 Prove tht the reciprocl lttice for the reciprocl lttice is the originl lttice.
More informationExample A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding
1 Exmple A rectngulr box without lid is to be mde from squre crdbord of sides 18 cm by cutting equl squres from ech corner nd then folding up the sides. 1 Exmple A rectngulr box without lid is to be mde
More informationMath 135 Circles and Completing the Square Examples
Mth 135 Circles nd Completing the Squre Exmples A perfect squre is number such tht = b 2 for some rel number b. Some exmples of perfect squres re 4 = 2 2, 16 = 4 2, 169 = 13 2. We wish to hve method for
More informationEQUATIONS OF LINES AND PLANES
EQUATIONS OF LINES AND PLANES MATH 195, SECTION 59 (VIPUL NAIK) Corresponding mteril in the ook: Section 12.5. Wht students should definitely get: Prmetric eqution of line given in point-direction nd twopoint
More informationBinary Representation of Numbers Autar Kaw
Binry Representtion of Numbers Autr Kw After reding this chpter, you should be ble to: 1. convert bse- rel number to its binry representtion,. convert binry number to n equivlent bse- number. In everydy
More information19. The Fermat-Euler Prime Number Theorem
19. The Fermt-Euler Prime Number Theorem Every prime number of the form 4n 1 cn be written s sum of two squres in only one wy (side from the order of the summnds). This fmous theorem ws discovered bout
More informationFUNCTIONS AND EQUATIONS. xεs. The simplest way to represent a set is by listing its members. We use the notation
FUNCTIONS AND EQUATIONS. SETS AND SUBSETS.. Definition of set. A set is ny collection of objects which re clled its elements. If x is n element of the set S, we sy tht x belongs to S nd write If y does
More informationHomework 3 Solutions
CS 341: Foundtions of Computer Science II Prof. Mrvin Nkym Homework 3 Solutions 1. Give NFAs with the specified numer of sttes recognizing ech of the following lnguges. In ll cses, the lphet is Σ = {,1}.
More informationFactoring Polynomials
Fctoring Polynomils Some definitions (not necessrily ll for secondry school mthemtics): A polynomil is the sum of one or more terms, in which ech term consists of product of constnt nd one or more vribles
More informationNovel Methods of Generating Self-Invertible Matrix for Hill Cipher Algorithm
Bibhudendr chry, Girij Snkr Rth, Srt Kumr Ptr, nd Sroj Kumr Pnigrhy Novel Methods of Generting Self-Invertible Mtrix for Hill Cipher lgorithm Bibhudendr chry Deprtment of Electronics & Communiction Engineering
More informationPROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY
MAT 0630 INTERNET RESOURCES, REVIEW OF CONCEPTS AND COMMON MISTAKES PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY Contents 1. ACT Compss Prctice Tests 1 2. Common Mistkes 2 3. Distributive
More information5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one.
5.2. LINE INTEGRALS 265 5.2 Line Integrls 5.2.1 Introduction Let us quickly review the kind of integrls we hve studied so fr before we introduce new one. 1. Definite integrl. Given continuous rel-vlued
More informationLecture 3 Gaussian Probability Distribution
Lecture 3 Gussin Probbility Distribution Introduction l Gussin probbility distribution is perhps the most used distribution in ll of science. u lso clled bell shped curve or norml distribution l Unlike
More informationTreatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3.
The nlysis of vrince (ANOVA) Although the t-test is one of the most commonly used sttisticl hypothesis tests, it hs limittions. The mjor limittion is tht the t-test cn be used to compre the mens of only
More information4 Approximations. 4.1 Background. D. Levy
D. Levy 4 Approximtions 4.1 Bckground In this chpter we re interested in pproximtion problems. Generlly speking, strting from function f(x) we would like to find different function g(x) tht belongs to
More informationRegular Sets and Expressions
Regulr Sets nd Expressions Finite utomt re importnt in science, mthemtics, nd engineering. Engineers like them ecuse they re super models for circuits (And, since the dvent of VLSI systems sometimes finite
More informationBabylonian Method of Computing the Square Root: Justifications Based on Fuzzy Techniques and on Computational Complexity
Bbylonin Method of Computing the Squre Root: Justifictions Bsed on Fuzzy Techniques nd on Computtionl Complexity Olg Koshelev Deprtment of Mthemtics Eduction University of Texs t El Pso 500 W. University
More informationIntegration by Substitution
Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is
More informationUse Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions.
Lerning Objectives Loci nd Conics Lesson 3: The Ellipse Level: Preclculus Time required: 120 minutes In this lesson, students will generlize their knowledge of the circle to the ellipse. The prmetric nd
More informationMathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100
hsn.uk.net Higher Mthemtics UNIT 3 OUTCOME 1 Vectors Contents Vectors 18 1 Vectors nd Sclrs 18 Components 18 3 Mgnitude 130 4 Equl Vectors 131 5 Addition nd Subtrction of Vectors 13 6 Multipliction by
More informationLectures 8 and 9 1 Rectangular waveguides
1 Lectures 8 nd 9 1 Rectngulr wveguides y b x z Consider rectngulr wveguide with 0 < x b. There re two types of wves in hollow wveguide with only one conductor; Trnsverse electric wves
More informationRIGHT TRIANGLES AND THE PYTHAGOREAN TRIPLETS
RIGHT TRIANGLES AND THE PYTHAGOREAN TRIPLETS Known for over 500 yers is the fct tht the sum of the squres of the legs of right tringle equls the squre of the hypotenuse. Tht is +b c. A simple proof is
More informationSPECIAL PRODUCTS AND FACTORIZATION
MODULE - Specil Products nd Fctoriztion 4 SPECIAL PRODUCTS AND FACTORIZATION In n erlier lesson you hve lernt multipliction of lgebric epressions, prticulrly polynomils. In the study of lgebr, we come
More informationOr more simply put, when adding or subtracting quantities, their uncertainties add.
Propgtion of Uncertint through Mthemticl Opertions Since the untit of interest in n eperiment is rrel otined mesuring tht untit directl, we must understnd how error propgtes when mthemticl opertions re
More informationg(y(a), y(b)) = o, B a y(a)+b b y(b)=c, Boundary Value Problems Lecture Notes to Accompany
Lecture Notes to Accompny Scientific Computing An Introductory Survey Second Edition by Michel T Heth Boundry Vlue Problems Side conditions prescribing solution or derivtive vlues t specified points required
More informationOperations with Polynomials
38 Chpter P Prerequisites P.4 Opertions with Polynomils Wht you should lern: Write polynomils in stndrd form nd identify the leding coefficients nd degrees of polynomils Add nd subtrct polynomils Multiply
More information1.00/1.001 Introduction to Computers and Engineering Problem Solving Fall 2011 - Final Exam
1./1.1 Introduction to Computers nd Engineering Problem Solving Fll 211 - Finl Exm Nme: MIT Emil: TA: Section: You hve 3 hours to complete this exm. In ll questions, you should ssume tht ll necessry pckges
More informationUNIVERSITY OF OSLO FACULTY OF MATHEMATICS AND NATURAL SCIENCES
UNIVERSITY OF OSLO FACULTY OF MATHEMATICS AND NATURAL SCIENCES Solution to exm in: FYS30, Quntum mechnics Dy of exm: Nov. 30. 05 Permitted mteril: Approved clcultor, D.J. Griffiths: Introduction to Quntum
More information6.2 Volumes of Revolution: The Disk Method
mth ppliction: volumes of revolution, prt ii Volumes of Revolution: The Disk Method One of the simplest pplictions of integrtion (Theorem ) nd the ccumultion process is to determine so-clled volumes of
More information1.2 The Integers and Rational Numbers
.2. THE INTEGERS AND RATIONAL NUMBERS.2 The Integers n Rtionl Numers The elements of the set of integers: consist of three types of numers: Z {..., 5, 4, 3, 2,, 0,, 2, 3, 4, 5,...} I. The (positive) nturl
More informationThe Velocity Factor of an Insulated Two-Wire Transmission Line
The Velocity Fctor of n Insulted Two-Wire Trnsmission Line Problem Kirk T. McDonld Joseph Henry Lbortories, Princeton University, Princeton, NJ 08544 Mrch 7, 008 Estimte the velocity fctor F = v/c nd the
More information9 CONTINUOUS DISTRIBUTIONS
9 CONTINUOUS DISTIBUTIONS A rndom vrible whose vlue my fll nywhere in rnge of vlues is continuous rndom vrible nd will be ssocited with some continuous distribution. Continuous distributions re to discrete
More information2005-06 Second Term MAT2060B 1. Supplementary Notes 3 Interchange of Differentiation and Integration
Source: http://www.mth.cuhk.edu.hk/~mt26/mt26b/notes/notes3.pdf 25-6 Second Term MAT26B 1 Supplementry Notes 3 Interchnge of Differentition nd Integrtion The theme of this course is bout vrious limiting
More informationMath 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1.
Mth 4, Homework Assignment. Prove tht two nonverticl lines re perpendiculr if nd only if the product of their slopes is. Proof. Let l nd l e nonverticl lines in R of slopes m nd m, respectively. Suppose
More informationRadius of the Earth - Radii Used in Geodesy James R. Clynch February 2006
dius of the Erth - dii Used in Geodesy Jmes. Clynch Februry 006 I. Erth dii Uses There is only one rdius of sphere. The erth is pproximtely sphere nd therefore, for some cses, this pproximtion is dequte.
More informationA.7.1 Trigonometric interpretation of dot product... 324. A.7.2 Geometric interpretation of dot product... 324
A P P E N D I X A Vectors CONTENTS A.1 Scling vector................................................ 321 A.2 Unit or Direction vectors...................................... 321 A.3 Vector ddition.................................................
More informationAlgebra Review. How well do you remember your algebra?
Algebr Review How well do you remember your lgebr? 1 The Order of Opertions Wht do we men when we write + 4? If we multiply we get 6 nd dding 4 gives 10. But, if we dd + 4 = 7 first, then multiply by then
More informationAppendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered:
Appendi D: Completing the Squre nd the Qudrtic Formul Fctoring qudrtic epressions such s: + 6 + 8 ws one of the topics introduced in Appendi C. Fctoring qudrtic epressions is useful skill tht cn help you
More informationPhysics 43 Homework Set 9 Chapter 40 Key
Physics 43 Homework Set 9 Chpter 4 Key. The wve function for n electron tht is confined to x nm is. Find the normliztion constnt. b. Wht is the probbility of finding the electron in. nm-wide region t x
More informationBasic Analysis of Autarky and Free Trade Models
Bsic Anlysis of Autrky nd Free Trde Models AUTARKY Autrky condition in prticulr commodity mrket refers to sitution in which country does not engge in ny trde in tht commodity with other countries. Consequently
More informationAll pay auctions with certain and uncertain prizes a comment
CENTER FOR RESEARC IN ECONOMICS AND MANAGEMENT CREAM Publiction No. 1-2015 All py uctions with certin nd uncertin prizes comment Christin Riis All py uctions with certin nd uncertin prizes comment Christin
More informationQUADRATURE METHODS. July 19, 2011. Kenneth L. Judd. Hoover Institution
QUADRATURE METHODS Kenneth L. Judd Hoover Institution July 19, 2011 1 Integrtion Most integrls cnnot be evluted nlyticlly Integrls frequently rise in economics Expected utility Discounted utility nd profits
More informationReview guide for the final exam in Math 233
Review guide for the finl exm in Mth 33 1 Bsic mteril. This review includes the reminder of the mteril for mth 33. The finl exm will be cumultive exm with mny of the problems coming from the mteril covered
More informationUnambiguous Recognizable Two-dimensional Languages
Unmbiguous Recognizble Two-dimensionl Lnguges Mrcell Anselmo, Dor Gimmrresi, Mri Mdoni, Antonio Restivo (Univ. of Slerno, Univ. Rom Tor Vergt, Univ. of Ctni, Univ. of Plermo) W2DL, My 26 REC fmily I REC
More informationCURVES ANDRÉ NEVES. that is, the curve α has finite length. v = p q p q. a i.e., the curve of smallest length connecting p to q is a straight line.
CURVES ANDRÉ NEVES 1. Problems (1) (Ex 1 of 1.3 of Do Crmo) Show tht the tngent line to the curve α(t) (3t, 3t 2, 2t 3 ) mkes constnt ngle with the line z x, y. (2) (Ex 6 of 1.3 of Do Crmo) Let α(t) (e
More information9.3. The Scalar Product. Introduction. Prerequisites. Learning Outcomes
The Sclr Product 9.3 Introduction There re two kinds of multipliction involving vectors. The first is known s the sclr product or dot product. This is so-clled becuse when the sclr product of two vectors
More informationSection 7-4 Translation of Axes
62 7 ADDITIONAL TOPICS IN ANALYTIC GEOMETRY Section 7-4 Trnsltion of Aes Trnsltion of Aes Stndrd Equtions of Trnslted Conics Grphing Equtions of the Form A 2 C 2 D E F 0 Finding Equtions of Conics In the
More informationAA1H Calculus Notes Math1115, Honours 1 1998. John Hutchinson
AA1H Clculus Notes Mth1115, Honours 1 1998 John Hutchinson Author ddress: Deprtment of Mthemtics, School of Mthemticl Sciences, Austrlin Ntionl University E-mil ddress: John.Hutchinson@nu.edu.u Contents
More informationSolution to Problem Set 1
CSE 5: Introduction to the Theory o Computtion, Winter A. Hevi nd J. Mo Solution to Prolem Set Jnury, Solution to Prolem Set.4 ). L = {w w egin with nd end with }. q q q q, d). L = {w w h length t let
More informationReasoning to Solve Equations and Inequalities
Lesson4 Resoning to Solve Equtions nd Inequlities In erlier work in this unit, you modeled situtions with severl vriles nd equtions. For exmple, suppose you were given usiness plns for concert showing
More informationModule Summary Sheets. C3, Methods for Advanced Mathematics (Version B reference to new book) Topic 2: Natural Logarithms and Exponentials
MEI Mthemtics in Ection nd Instry Topic : Proof MEI Structured Mthemtics Mole Summry Sheets C, Methods for Anced Mthemtics (Version B reference to new book) Topic : Nturl Logrithms nd Eponentils Topic
More informationINTERCHANGING TWO LIMITS. Zoran Kadelburg and Milosav M. Marjanović
THE TEACHING OF MATHEMATICS 2005, Vol. VIII, 1, pp. 15 29 INTERCHANGING TWO LIMITS Zorn Kdelburg nd Milosv M. Mrjnović This pper is dedicted to the memory of our illustrious professor of nlysis Slobodn
More informationSection 5-4 Trigonometric Functions
5- Trigonometric Functions Section 5- Trigonometric Functions Definition of the Trigonometric Functions Clcultor Evlution of Trigonometric Functions Definition of the Trigonometric Functions Alternte Form
More informationBayesian Updating with Continuous Priors Class 13, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom
Byesin Updting with Continuous Priors Clss 3, 8.05, Spring 04 Jeremy Orloff nd Jonthn Bloom Lerning Gols. Understnd prmeterized fmily of distriutions s representing continuous rnge of hypotheses for the
More informationDistributions. (corresponding to the cumulative distribution function for the discrete case).
Distributions Recll tht n integrble function f : R [,] such tht R f()d = is clled probbility density function (pdf). The distribution function for the pdf is given by F() = (corresponding to the cumultive
More informationLinear Equations in Two Variables
Liner Equtions in Two Vribles In this chpter, we ll use the geometry of lines to help us solve equtions. Liner equtions in two vribles If, b, ndr re rel numbers (nd if nd b re not both equl to 0) then
More informationThe remaining two sides of the right triangle are called the legs of the right triangle.
10 MODULE 6. RADICAL EXPRESSIONS 6 Pythgoren Theorem The Pythgoren Theorem An ngle tht mesures 90 degrees is lled right ngle. If one of the ngles of tringle is right ngle, then the tringle is lled right
More informationBrillouin Zones. Physics 3P41 Chris Wiebe
Brillouin Zones Physics 3P41 Chris Wiebe Direct spce to reciprocl spce * = 2 i j πδ ij Rel (direct) spce Reciprocl spce Note: The rel spce nd reciprocl spce vectors re not necessrily in the sme direction
More informationExperiment 6: Friction
Experiment 6: Friction In previous lbs we studied Newton s lws in n idel setting, tht is, one where friction nd ir resistnce were ignored. However, from our everydy experience with motion, we know tht
More information. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2
7 CHAPTER THREE. Cross Product Given two vectors = (,, nd = (,, in R, the cross product of nd written! is defined to e: " = (!,!,! Note! clled cross is VECTOR (unlike which is sclr. Exmple (,, " (4,5,6
More informationRotating DC Motors Part II
Rotting Motors rt II II.1 Motor Equivlent Circuit The next step in our consiertion of motors is to evelop n equivlent circuit which cn be use to better unerstn motor opertion. The rmtures in rel motors
More informationbody.allow-sidebar OR.no-sidebar.home-page (if this is the home page).has-custom-banner OR.nocustom-banner .IR OR.no-IR
body.llow-sidebr OR.no-sidebr.home-pge (if this is the home pge).hs-custom-bnner OR.nocustom-bnner.IR OR.no-IR #IDENTIFIER_FOR_THIS_SITE div#pge-continer.depends_on_page_ty PE llow-sidebr mens tht there
More informationPhysics 6010, Fall 2010 Symmetries and Conservation Laws: Energy, Momentum and Angular Momentum Relevant Sections in Text: 2.6, 2.
Physics 6010, Fll 2010 Symmetries nd Conservtion Lws: Energy, Momentum nd Angulr Momentum Relevnt Sections in Text: 2.6, 2.7 Symmetries nd Conservtion Lws By conservtion lw we men quntity constructed from
More informationScalar and Vector Quantities. A scalar is a quantity having only magnitude (and possibly phase). LECTURE 2a: VECTOR ANALYSIS Vector Algebra
Sclr nd Vector Quntities : VECTO NLYSIS Vector lgebr sclr is quntit hving onl mgnitude (nd possibl phse). Emples: voltge, current, chrge, energ, temperture vector is quntit hving direction in ddition to
More informationCHAPTER 11 Numerical Differentiation and Integration
CHAPTER 11 Numericl Differentition nd Integrtion Differentition nd integrtion re bsic mthemticl opertions with wide rnge of pplictions in mny res of science. It is therefore importnt to hve good methods
More informationHow To Understand The Theory Of Inequlities
Ostrowski Type Inequlities nd Applictions in Numericl Integrtion Edited By: Sever S Drgomir nd Themistocles M Rssis SS Drgomir) School nd Communictions nd Informtics, Victori University of Technology,
More informationPentominoes. Pentominoes. Bruce Baguley Cascade Math Systems, LLC. The pentominoes are a simple-looking set of objects through which some powerful
Pentominoes Bruce Bguley Cscde Mth Systems, LLC Astrct. Pentominoes nd their reltives the polyominoes, polycues, nd polyhypercues will e used to explore nd pply vrious importnt mthemticl concepts. In this
More informationVectors. The magnitude of a vector is its length, which can be determined by Pythagoras Theorem. The magnitude of a is written as a.
Vectors mesurement which onl descries the mgnitude (i.e. size) of the oject is clled sclr quntit, e.g. Glsgow is 11 miles from irdrie. vector is quntit with mgnitude nd direction, e.g. Glsgow is 11 miles
More informationExam 1 Study Guide. Differentiation and Anti-differentiation Rules from Calculus I
Exm Stuy Guie Mth 2020 - Clculus II, Winter 204 The following is list of importnt concepts from ech section tht will be teste on exm. This is not complete list of the mteril tht you shoul know for the
More informationCS99S Laboratory 2 Preparation Copyright W. J. Dally 2001 October 1, 2001
CS99S Lortory 2 Preprtion Copyright W. J. Dlly 2 Octoer, 2 Ojectives:. Understnd the principle of sttic CMOS gte circuits 2. Build simple logic gtes from MOS trnsistors 3. Evlute these gtes to oserve logic
More informationLec 2: Gates and Logic
Lec 2: Gtes nd Logic Kvit Bl CS 34, Fll 28 Computer Science Cornell University Announcements Clss newsgroup creted Posted on we-pge Use it for prtner finding First ssignment is to find prtners Due this
More informationOne Minute To Learn Programming: Finite Automata
Gret Theoreticl Ides In Computer Science Steven Rudich CS 15-251 Spring 2005 Lecture 9 Fe 8 2005 Crnegie Mellon University One Minute To Lern Progrmming: Finite Automt Let me tech you progrmming lnguge
More informationWarm-up for Differential Calculus
Summer Assignment Wrm-up for Differentil Clculus Who should complete this pcket? Students who hve completed Functions or Honors Functions nd will be tking Differentil Clculus in the fll of 015. Due Dte:
More informationReal Analysis and Multivariable Calculus: Graduate Level Problems and Solutions. Igor Yanovsky
Rel Anlysis nd Multivrible Clculus: Grdute Level Problems nd Solutions Igor Ynovsky 1 Rel Anlysis nd Multivrible Clculus Igor Ynovsky, 2005 2 Disclimer: This hndbook is intended to ssist grdute students
More informationThe Riemann Integral. Chapter 1
Chpter The Riemnn Integrl now of some universities in Englnd where the Lebesgue integrl is tught in the first yer of mthemtics degree insted of the Riemnn integrl, but now of no universities in Englnd
More informationQuick Reference Guide: One-time Account Update
Quick Reference Guide: One-time Account Updte How to complete The Quick Reference Guide shows wht existing SingPss users need to do when logging in to the enhnced SingPss service for the first time. 1)
More informationKarlstad University. Division for Engineering Science, Physics and Mathematics. Yury V. Shestopalov and Yury G. Smirnov. Integral Equations
Krlstd University Division for Engineering Science, Physics nd Mthemtics Yury V. Shestoplov nd Yury G. Smirnov Integrl Equtions A compendium Krlstd Contents 1 Prefce 4 Notion nd exmples of integrl equtions
More informationwww.mathsbox.org.uk e.g. f(x) = x domain x 0 (cannot find the square root of negative values)
www.mthsbo.org.uk CORE SUMMARY NOTES Functions A function is rule which genertes ectl ONE OUTPUT for EVERY INPUT. To be defined full the function hs RULE tells ou how to clculte the output from the input
More informationChapter 04.05 System of Equations
hpter 04.05 System of Equtios After redig th chpter, you should be ble to:. setup simulteous lier equtios i mtrix form d vice-vers,. uderstd the cocept of the iverse of mtrix, 3. kow the differece betwee
More information6 Energy Methods And The Energy of Waves MATH 22C
6 Energy Methods And The Energy of Wves MATH 22C. Conservtion of Energy We discuss the principle of conservtion of energy for ODE s, derive the energy ssocited with the hrmonic oscilltor, nd then use this
More informationM5A42 APPLIED STOCHASTIC PROCESSES PROBLEM SHEET 1 SOLUTIONS Term 1 2010-2011
M5A42 APPLIED STOCHASTIC PROCESSES PROBLEM SHEET 1 SOLUTIONS Term 1 21-211 1. Clculte the men, vrince nd chrcteristic function of the following probbility density functions. ) The exponentil distribution
More information1B METHODS LECTURE NOTES. PART I: Fourier series, Self adjoint ODEs
1B Methods 1. 1B METHODS ECTURE NOTES Richrd Jozs, DAMTP Cmbridge rj31@cm.c.uk October 213 PART I: Fourier series, Self djoint ODEs 1B Methods 2 PREFACE These notes (in four prts cover the essentil content
More informationSmall Business Networking
Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology
More informationGeometry 7-1 Geometric Mean and the Pythagorean Theorem
Geometry 7-1 Geometric Men nd the Pythgoren Theorem. Geometric Men 1. Def: The geometric men etween two positive numers nd is the positive numer x where: = x. x Ex 1: Find the geometric men etween the
More information0.1 Basic Set Theory and Interval Notation
0.1 Bsic Set Theory nd Intervl Nottion 3 0.1 Bsic Set Theory nd Intervl Nottion 0.1.1 Some Bsic Set Theory Notions Like ll good Mth ooks, we egin with definition. Definition 0.1. A set is well-defined
More information2 DIODE CLIPPING and CLAMPING CIRCUITS
2 DIODE CLIPPING nd CLAMPING CIRCUITS 2.1 Ojectives Understnding the operting principle of diode clipping circuit Understnding the operting principle of clmping circuit Understnding the wveform chnge of
More informationOptiml Control of Seril, Multi-Echelon Inventory (E&I) & Mixed Erlng demnds
Optiml Control of Seril, Multi-Echelon Inventory/Production Systems with Periodic Btching Geert-Jn vn Houtum Deprtment of Technology Mngement, Technische Universiteit Eindhoven, P.O. Box 513, 56 MB, Eindhoven,
More informationDrawing Diagrams From Labelled Graphs
Drwing Digrms From Lbelled Grphs Jérôme Thièvre 1 INA, 4, venue de l Europe, 94366 BRY SUR MARNE FRANCE Anne Verroust-Blondet 2 INRIA Rocquencourt, B.P. 105, 78153 LE CHESNAY Cedex FRANCE Mrie-Luce Viud
More information2.016 Hydrodynamics Prof. A.H. Techet
.01 Hydrodynics Reding #.01 Hydrodynics Prof. A.H. Techet Added Mss For the cse of unstedy otion of bodies underwter or unstedy flow round objects, we ust consider the dditionl effect (force) resulting
More information