Unit 5. Hypersurfaces

Size: px
Start display at page:

Download "Unit 5. Hypersurfaces"

Transcription

1 Uit 5. Hyersurfaces ================================================================= Vector fields alog hyersurfaces, tagetial vector fields, derivatios of vector fields with resect to a taget directio, the Weigarte ma, biliear forms, the first ad secod fudametal forms of a hyersurface, ricial directios ad ricial curvatures, mea curvature ad the Gaussia curvature, Euler s formula Defiitio. Let r:w l R be a arameterized hyersurface. A vector field alog the hyersurface is a maig X:W L T R from the domai of arameters * ito the taget budle of R such that X(u) e T R for ay u e W. X is a r(u) tagetial vector field, if X(u) is taget to the hyersurface at r(u) ~ ~ Sice X(u) has the form (r(u),x(u)), where X:W L R, there is a oe to oe corresodece betwee vector fields alog a arameterized hyersurface ad smooth maigs of the domai of arameters ito R. Roughly seakig, if we are give a smooth maig of the arameter domai ito R, we may thik of it as a vector field alog the hyersurface though formally it is ot a vector field. I this way, the maigs r,...,r ad N should be thought 1-1 of as vector fields alog the hyersurface, the first -1 of which are tagetial. Give a vector field alog a hyersurface, we would like to exress the seed of chage of the vector field vectors as we move alog the surface, i terms of the seed of our motio. This is achieved by the followig. Defiitio. Let r:w l R be a arameterized hyersurface, X:W L R be a vector field alog it, u e W, v a taget vector of the hyersurface at 0 r(u ). We defie the derivative d X of the vector field X i the directio v v as d X = (Xqu) (0), where u: [-1,1] L W is a curve i the arameter domai v such that u(0) = u ad (rqu) (0) = v. 0 Sice by the chai rule -1 (Xqu) (0) = S u (0) X (u(0)), i i where (u,...,u ) are the comoets of u, X,...,X are the artial derivatives of X, ad by -1 v = (rqu) (0) = S u (0) r (u(0)) i i 1

2 the umbers u (0),...,u (0) 1-1 are the comoets of v i the basis r (u ),...,r (u ) of the taget sace at r(u ), 0 we have the followig formula -1 d X = S v X (u ), v i i 0 where v,...,v 1-1 are the comoets of the vector v i the basis r (u ),..., 1 0 r (u ) This formula shows that the defiitio of d X v is correct, i.e. ideedet of the choice of the curve u(t). We shall cosider the local behavior of curvature o a hyersurface. The way i which a hyersurface curves aroud i R is closely related to the way the ormal directio chages as we move from oit to oit. Lemma. The derivative d N of the ormal directio o a hyersurface with v resect to a taget vector v at = r(u) is taget to the hyersurface at r(u). Proof. We eed to show that d N is orthogoal to N(). Ideed, Y differetiatig the relatio 1 _ < N, N >, we get 0 = < d N, N > + < N, d N > = 2 < d N, N > v v v Defiitio. Let us deote by M the arameterized hyersurface r:w l R ad by T M the liear sace of its taget vectors at = r(u ). 0 The liear ma defied for a fixed e M by L : T M L T M L (v) = - d N v is called the Weigarte ma or shae oerator of M at Before goig o with the study of hyersurfaces, let us recall some defiitios from liear algebra. Defiitio. Let V be a vector sace. A biliear fuctio or form o V is a maig satisfyig the idetities B : VxV L R B(ax +bx,y) = a B(x,y) + b B(x,y), B(x,ay +by ) = a B(x,y ) + b B(x,y ) for ay x,x,x,y,y,y ev, a,ber B is said to be symmetric if B(x,y) = B(y,x) for all x y e V. A symmetric biliear fuctio is ositive defiite if B(x,x) >0 for x$ A vector sace equied with a ositive defiite symmetric biliear form is a Euclidea vector sace

3 For examle, R with the usual dot roduct o it is a Euclidea vector sace. If x,...,x is a basis of the vector sace V ad B is a biliear fuctio 1 o V the the x matrix (b ) with etries b = B(x,x ) is called the ij ij i j matrix reresetatio of B with resect to the basis x,...,x. Fixig the basis we get a oe to oe corresodece betwee biliear fuctios ad x matrices. A biliear form is symmetric if ad oly if its matrix reresetatio with resect to a basis is symmetric. Defiitio. The quadratic form of a biliear fuctio B is the fuctio defied by the equality Q (x) = B(x,x). B Symmetric biliear fuctios ca be recovered from their quadratic forms with the hel of the idetity 1 B(x,y) = (Q (x+y) - Q (x) - Q (y)). 2 B B B Now we retur to hyersurfaces. We defie two biliear forms o each taget sace of the hyersurface Defiitio. Let M be a arameterized hyersurface r:w l R, u e W, T M the liear sace of taget vectors of M at = r(u), L :T M L T M the Weigarte ma. The first fudametal form of the hyersurface is the biliear fuctio I o T M obtaied by restrictio of the dot roduct oto T M I (v,w) = < v, w > for v,w e T M. The secod fudametal form of the hyersurface is the biliear fuctio II o T M defied by the equality II (v,w) = < L v, w > for v,w e T M. The first fudametal form is obviously a ositive defiite symmetric biliear fuctio o the taget sace. Its matrix reresetatio with resect to the basis r (u ),...,r (u ) has etries < r (u ), r (u ) > i 0 j 0 A imortat roerty of the Weigarte ma ad the secod fudametal form is stated i the followig theorem. Theorem. The secod fudametal form is symmetric, i.e < L v, w > = < v, L w > for v,w e T M, or i other words, the Weigarte ma is self-adjoit (with resect to the first fudametal form). Proof. It is eough to rove that the matrix of the secod fudametal form with resect to the basis r (u ),...,r (u ) is symmetric Lemma. II (r (u ),r (u )) = < r (u ), N(u ) > i 0 j 0 ij 0 0 Proof of Lemma. We kow that the ormal vector field N is eredicular to

4 ay tagetial vector field, thus < N, r > _ 0. j Differetiatig this idetity with resect to the i-th arameter we get from which < d N, r > + < N, r > _ 0, r j ji i < N, r > _ < - d N, r > = < L r, r > ji r j r i j i Sice by Youg s theorem r = r, the lemma shows that the matrix of the ij ji secod fudametal form is symmetric Comarig the idetity roved i the lemma with the formula exressig the ormal curvature of the hyersurface i a taget directio v we see that the ormal curvature is the quotiet of the quadratic forms of the secod ad first fudametal forms -1-1 S S <N(u ),r (u )>v v 0 ij 0 i j II (v,v) j=1 k(v) = = , 2 I (v,v) v -1 where v = S v r (u ) is a taget vector of the hyersurface at = r(u ). i i 0 0 The exressio u o II (v,v) k(v) = I (v,v) m gives rise to a liear algebraic ivestigatio of the ormal curvature. It is atural to ask at which directios the ormal curvature attais its extrema. Sice k(lv) = k(v) for ay l $ 0, it is eough to cosider this questio for the restrictio of k oto the uit shere S i the taget sace. The uit shere of a Euclidea sace is a comact (=closed ad bouded) subset, thus by Weierstrass theorem, ay cotiuous fuctio defied o it attais its maximum ad miimum. Defiitio. Let f be a differetiable fuctio defied o the uit shere S of a Euclidea vector sace. We say that the vector v e S is a critical oit of f if for ay curve g : [-1,1] L S o the shere such that g(0) = v the derivative of the comosite fuctio fqg vaishes at 0. Clearly, local miimum ad maximum oits of a fuctio are its critical oits, but the coverse is ot true. The followig roositio gives a characterizatio of critical oits for the restrictio of the ormal curvature oto the uit shere of the taget sace. 4

5 Proositio. Let V be a fiite dimesioal vector sace with a ositive defiite symmetric biliear fuctio <,> ad let L:V L V be a self-adjoit liear trasformatio o V. Let S = {x e V : <x,x> = 1} ad defie f:s l R by f(x)=<lx,x>. The v e S is a critical oit of f if ad oly if v is a eigevector of L. Proof. For ay curve g:[-1,1] l S such that g(0) = v, we have d <L(g(t)),g(t)>1 = <L(g (0)),g(0)>+<L(g(0)),g (0)> d t t=0 = <Lg (0),v>+<Lv,g (0)> = 2 <Lv,g (0)>. This meas that v is a critical oit of f if ad oly if Lv is orthogoal to every vectors of the form g (0). Sice the seed vectors g (0) of sherical curves through v = g(0) rage over the taget sace of the shere S, v is a critical oit of f if ad oly if Lv is orthogoal to the taget sace of S at v however, sice the ormal vector of this taget sace is v, the latter coditio is satisfied if ad oly if Lv is a scalar multile of v, i.e. v is a eigevector of L As a alicatio of the roositio, let us rove the followig theorem of liear algebra. Theorem. Let V be a fiite dimesioal Euclidea vector sace ad let L : V L V be a self-adjoit liear trasformatio o V. The there exists a orthoormal basis of V cosistig of eigevectors of L. Proof. By iductio o the dimesio of V. For = 1 the theorem is trivial. Assume that it is true for = k. Suose = k + 1. By the roositio, there exists a uit vector v i V which is a eigevector of L. 1 1 Let W = v = {w e V : v 1 w }. The L(W) c W sice we have 1 1 <Lw,v > = <w,lv > = <w,l v > = l <w,v > = for ay w e W, where l is the eigevalue belogig to v. Clearly L1 is 1 1 W self-adjoit. Sice dim(w) = dim(v) - 1 = k, the iductio assumtio imlies that there exists a orthoormal basis (v,...,v ) for W cosistig of 2 eigevectors of L1. But each eigevector of L1 is a eigevector of L, so W (v,...,v ) is a orthoormal basis for V cosistig of eigevectors of L Defiitio. For a hyersurface M i R arameterized by r, r(u ) = e M, the eigevalues k (),...,k () of the Weigarte ma L :T M LT M are 1-1 called the ricial curvatures of M at, the uit eigevectors of L are called ricial curvature directios If the ricial curvatures are ordered so that k ()<k ()<...<k (), the discussio above shows that k () is the maximal, k () is the miimal -1 1 value of the ormal curvature k(v). W 5

6 Theorem. (Euler s formula) Let v,...,v be a orthoormal basis of T M cosistig of ricial curvature directios, k (),...,k () be the 1-1 corresodig ricial curvatures. The the ormal curvature k(v) i the directio v e T M, N v N = 1, is give by k(y) = S k () <Y,Y > = S k () cos (q ), i i i i where q = arc cos(<v,v >) is the agle betwee v ad v. i i i Proof. Sice (v,...,v ) is a orthoormal basis, the vector v ca be exressed as -1 v = S <v,v > v. i i Makig use of this formula, we obtai -1-1 & * k(v) = <L (v),v> = <L S <v,v > v, S <v,v > v > = 7 i i8 i i = < S <v,v > k () v, S <v,v > v > = S k () <v,v > i i i i i i i The determiat ad trace of the Weigarte ma, that is the roduct ad sum of the ricial curvatures are of articular imortace i differetial geometry. Defiitio. For M a hyersurface, e M, the determiat K() of the Weigarte ma L is called the Gaussia or Gauss-Kroecker curvature of M at , H() = 1/(-1) trace (L ) is called the mea curvature Whe we comute the ricial curvatures ad directios of a hyersurface at a oit we geerally work with a matrix reresetatio of the Weigarte ma. Recall that if V is a liear sace with basis x,...,x ad L:V L V is 1 a liear maig the the matrix reresetatio of V with resect to the basis x,...,x is the x matrix (l ) for which 1 ij L(x ) = S l x,2,...,. i ij j j=1 Whe we have a deal with a arameterized hyersurface r:w l R, it is atural to take the basis r (u),...,r (u) of the taget sace at r(u). Let 1-1 us deote by G = (g ), B = (b ) ad L = (l ) the matrix reresetatios of ij ij ij the first ad secod fudametal forms ad the Weigarte ma resectively, with resect to this basis ( g, b ad l are fuctios o the arameter ij ij ij domai). Comoets of G ad B ca be calculated accordig to the equatios g = < r, r >, ij i j b = < N, r > (cf. Lemma above). ij ij 6

7 The relatioshi betwee the matrices G, B, ad L follows from the followig equalities -1-1 b = < L r, r > = < S l r, r > = S l <r, r > = ij r i j ik k j ik k j k=1 k=1-1 = S l g ik kj k=1 exressig that B = L G. G is the matrix of a ositive defiite biliear fuctio, hece it is ivertible (its determiat is ositive). Multilyig the equatio B = L G with the iverse of G we get the exressio u o -1 L = B G m for the matrix of the Weigarte oerator. Corollary. The Gaussia curvature of a hyersurface is equal to u o det B K = det G m Recall from liear algebra that i order to determie the eigevalues of a liear maig with matrix reresetatio L oe has to fid the roots of the characteristic olyomial (l) = det (L - l I), where I deotes the idetity L matrix. Havig determied the eigevalues of the liear maig, comoets of eigevectors with resect to the fixed basis are obtaied as o-zero solutios of the liear system of equatios L v = l v where l is a ozero eigevalue of L. Further Exercices 5-1. Determie the Weigarte ma for a shere of radius r at oe of its oits Fid the ormal curvature k(v) for each taget directio v, the ricial curvatures ad the ricial curvature directios, ad comute the Gaussia ad mea curvatures of the followig surfaces at the give oit (x /a )+(x /b )+(x /c ) = 1, = (a,0,0) (ellisoid); (x /a )+(x /b )-(x /c ) = 1, = (a,0,0) (oe-sheeted hyerboloid); & 2 2 * x + r x +x - 2 = 1 = (0,3,0) or = (0,1,0) (torus). 7

8 5-3. Suose that the ricial curvatures of a arameterized surface 3 i R vaish. Show that the surface is a art of a lae Fid the Gaussia curvature K:M L R for the followig surfaces x +x -x = 0, x 3 > 0 (coe) (x /a )+(x /b )-(x /c ) = 1 (hyerboloid); (x /a )+(x /b )-x = 0 (ellitic araboloid); (x /a )-(x /b )-x = 0 (hyerbolic araboloid) Let M be a (hyer)surface i R, e M. Show that for each v,w e T M, L (v) x L (w) = K() v x w. 8

PAPER : IIT-JAM 2010

PAPER : IIT-JAM 2010 MATHEMATICS-MA (CODE A) Q.-Q.5: Oly oe optio is correct for each questio. Each questio carries (+6) marks for correct aswer ad ( ) marks for icorrect aswer.. Which of the followig coditios does NOT esure

More information

[ 47 ] then T ( m ) is true for all n a. 2. The greatest integer function : [ ] is defined by selling [ x]

[ 47 ] then T ( m ) is true for all n a. 2. The greatest integer function : [ ] is defined by selling [ x] [ 47 ] Number System 1. Itroductio Pricile : Let { T ( ) : N} be a set of statemets, oe for each atural umber. If (i), T ( a ) is true for some a N ad (ii) T ( k ) is true imlies T ( k 1) is true for all

More information

Continuity, Derivatives, and All That

Continuity, Derivatives, and All That Chater Seve Cotiuity, Derivatives, ad All That 7 imits ad Cotiuity et x R ad r > The set B( a; r) { x R : x a < r} is called the oe ball of radius r cetered at x The closed ball of radius r cetered at

More information

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j. Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α

More information

A brief introduction to linear algebra

A brief introduction to linear algebra CHAPTER 6 A brief itroductio to liear algebra 1. Vector spaces ad liear maps I what follows, fix K 2{Q, R, C}. More geerally, K ca be ay field. 1.1. Vector spaces. Motivated by our ituitio of addig ad

More information

Inverse Matrix. A meaning that matrix B is an inverse of matrix A.

Inverse Matrix. A meaning that matrix B is an inverse of matrix A. Iverse Matrix Two square matrices A ad B of dimesios are called iverses to oe aother if the followig holds, AB BA I (11) The otio is dual but we ofte write 1 B A meaig that matrix B is a iverse of matrix

More information

LECTURE 8: ORTHOGONALITY (CHAPTER 5 IN THE BOOK)

LECTURE 8: ORTHOGONALITY (CHAPTER 5 IN THE BOOK) LECTURE 8: ORTHOGONALITY (CHAPTER 5 IN THE BOOK) Everythig marked by is ot required by the course syllabus I this lecture, all vector spaces is over the real umber R. All vectors i R is viewed as a colum

More information

MATH10212 Linear Algebra B Proof Problems

MATH10212 Linear Algebra B Proof Problems MATH22 Liear Algebra Proof Problems 5 Jue 26 Each problem requests a proof of a simple statemet Problems placed lower i the list may use the results of previous oes Matrices ermiats If a b R the matrix

More information

Chapter 2. Periodic points of toral. automorphisms. 2.1 General introduction

Chapter 2. Periodic points of toral. automorphisms. 2.1 General introduction Chapter 2 Periodic poits of toral automorphisms 2.1 Geeral itroductio The automorphisms of the two-dimesioal torus are rich mathematical objects possessig iterestig geometric, algebraic, topological ad

More information

Orthogonal transformations

Orthogonal transformations Orthogoal trasformatios October 12, 2014 1 Defiig property The squared legth of a vector is give by takig the dot product of a vector with itself, v 2 v v g ij v i v j A orthogoal trasformatio is a liear

More information

n 3 ln n n ln n is convergent by p-series for p = 2 > 1. n2 Therefore we can apply Limit Comparison Test to determine lutely convergent.

n 3 ln n n ln n is convergent by p-series for p = 2 > 1. n2 Therefore we can apply Limit Comparison Test to determine lutely convergent. 06 微甲 0-04 06-0 班期中考解答和評分標準. ( poits) Determie whether the series is absolutely coverget, coditioally coverget, or diverget. Please state the tests which you use. (a) ( poits) (b) ( poits) (c) ( poits)

More information

Chapter 2. Finite Fields (Chapter 3 in the text)

Chapter 2. Finite Fields (Chapter 3 in the text) Chater 2. Fiite Fields (Chater 3 i the tet 1. Grou Structures 2. Costructios of Fiite Fields GF(2 ad GF( 3. Basic Theory of Fiite Fields 4. The Miimal Polyomials 5. Trace Fuctios 6. Subfields 1. Grou Structures

More information

SYMMETRIC POSITIVE SEMI-DEFINITE SOLUTIONS OF AX = B AND XC = D

SYMMETRIC POSITIVE SEMI-DEFINITE SOLUTIONS OF AX = B AND XC = D Joural of Pure ad Alied Mathematics: Advaces ad Alicatios olume, Number, 009, Pages 99-07 SYMMERIC POSIIE SEMI-DEFINIE SOLUIONS OF AX B AND XC D School of Mathematics ad Physics Jiagsu Uiversity of Sciece

More information

5.1. The Rayleigh s quotient. Definition 49. Let A = A be a self-adjoint matrix. quotient is the function. R(x) = x,ax, for x = 0.

5.1. The Rayleigh s quotient. Definition 49. Let A = A be a self-adjoint matrix. quotient is the function. R(x) = x,ax, for x = 0. 40 RODICA D. COSTIN 5. The Rayleigh s priciple ad the i priciple for the eigevalues of a self-adjoit matrix Eigevalues of self-adjoit matrices are easy to calculate. This sectio shows how this is doe usig

More information

Math Solutions to homework 6

Math Solutions to homework 6 Math 175 - Solutios to homework 6 Cédric De Groote November 16, 2017 Problem 1 (8.11 i the book): Let K be a compact Hermitia operator o a Hilbert space H ad let the kerel of K be {0}. Show that there

More information

For a 3 3 diagonal matrix we find. Thus e 1 is a eigenvector corresponding to eigenvalue λ = a 11. Thus matrix A has eigenvalues 2 and 3.

For a 3 3 diagonal matrix we find. Thus e 1 is a eigenvector corresponding to eigenvalue λ = a 11. Thus matrix A has eigenvalues 2 and 3. Closed Leotief Model Chapter 6 Eigevalues I a closed Leotief iput-output-model cosumptio ad productio coicide, i.e. V x = x = x Is this possible for the give techology matrix V? This is a special case

More information

ECE534, Spring 2018: Final Exam

ECE534, Spring 2018: Final Exam ECE534, Srig 2018: Fial Exam Problem 1 Let X N (0, 1) ad Y N (0, 1) be ideedet radom variables. variables V = X + Y ad W = X 2Y. Defie the radom (a) Are V, W joitly Gaussia? Justify your aswer. (b) Comute

More information

ALGEBRAIC GEOMETRY COURSE NOTES, LECTURE 5: SINGULARITIES.

ALGEBRAIC GEOMETRY COURSE NOTES, LECTURE 5: SINGULARITIES. ALGEBRAIC GEOMETRY COURSE NOTES, LECTURE 5: SINGULARITIES. ANDREW SALCH 1. The Jacobia criterio for osigularity. You have probably oticed by ow that some poits o varieties are smooth i a sese somethig

More information

, then cv V. Differential Equations Elements of Lineaer Algebra Name: Consider the differential equation. and y2 cos( kx)

, then cv V. Differential Equations Elements of Lineaer Algebra Name: Consider the differential equation. and y2 cos( kx) Cosider the differetial equatio y '' k y 0 has particular solutios y1 si( kx) ad y cos( kx) I geeral, ay liear combiatio of y1 ad y, cy 1 1 cy where c1, c is also a solutio to the equatio above The reaso

More information

Second day August 2, Problems and Solutions

Second day August 2, Problems and Solutions FOURTH INTERNATIONAL COMPETITION FOR UNIVERSITY STUDENTS IN MATHEMATICS July 30 August 4, 1997, Plovdiv, BULGARIA Secod day August, 1997 Problems ad Solutios Let Problem 1. Let f be a C 3 (R) o-egative

More information

Brief Review of Functions of Several Variables

Brief Review of Functions of Several Variables Brief Review of Fuctios of Several Variables Differetiatio Differetiatio Recall, a fuctio f : R R is differetiable at x R if ( ) ( ) lim f x f x 0 exists df ( x) Whe this limit exists we call it or f(

More information

Zeros of Polynomials

Zeros of Polynomials Math 160 www.timetodare.com 4.5 4.6 Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered with fidig the solutios of polyomial equatios of ay degree

More information

Final Solutions. 1. (25pts) Define the following terms. Be as precise as you can.

Final Solutions. 1. (25pts) Define the following terms. Be as precise as you can. Mathematics H104 A. Ogus Fall, 004 Fial Solutios 1. (5ts) Defie the followig terms. Be as recise as you ca. (a) (3ts) A ucoutable set. A ucoutable set is a set which ca ot be ut ito bijectio with a fiite

More information

CHAPTER 5. Theory and Solution Using Matrix Techniques

CHAPTER 5. Theory and Solution Using Matrix Techniques A SERIES OF CLASS NOTES FOR 2005-2006 TO INTRODUCE LINEAR AND NONLINEAR PROBLEMS TO ENGINEERS, SCIENTISTS, AND APPLIED MATHEMATICIANS DE CLASS NOTES 3 A COLLECTION OF HANDOUTS ON SYSTEMS OF ORDINARY DIFFERENTIAL

More information

ON SUPERSINGULAR ELLIPTIC CURVES AND HYPERGEOMETRIC FUNCTIONS

ON SUPERSINGULAR ELLIPTIC CURVES AND HYPERGEOMETRIC FUNCTIONS ON SUPERSINGULAR ELLIPTIC CURVES AND HYPERGEOMETRIC FUNCTIONS KEENAN MONKS Abstract The Legedre Family of ellitic curves has the remarkable roerty that both its eriods ad its suersigular locus have descritios

More information

CHAPTER I: Vector Spaces

CHAPTER I: Vector Spaces CHAPTER I: Vector Spaces Sectio 1: Itroductio ad Examples This first chapter is largely a review of topics you probably saw i your liear algebra course. So why cover it? (1) Not everyoe remembers everythig

More information

Review Problems 1. ICME and MS&E Refresher Course September 19, 2011 B = C = AB = A = A 2 = A 3... C 2 = C 3 = =

Review Problems 1. ICME and MS&E Refresher Course September 19, 2011 B = C = AB = A = A 2 = A 3... C 2 = C 3 = = Review Problems ICME ad MS&E Refresher Course September 9, 0 Warm-up problems. For the followig matrices A = 0 B = C = AB = 0 fid all powers A,A 3,(which is A times A),... ad B,B 3,... ad C,C 3,... Solutio:

More information

Classification of DT signals

Classification of DT signals Comlex exoetial A discrete time sigal may be comlex valued I digital commuicatios comlex sigals arise aturally A comlex sigal may be rereseted i two forms: jarg { z( ) } { } z ( ) = Re { z ( )} + jim {

More information

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row:

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row: Math 50-004 Tue Feb 4 Cotiue with sectio 36 Determiats The effective way to compute determiats for larger-sized matrices without lots of zeroes is to ot use the defiitio, but rather to use the followig

More information

NBHM QUESTION 2007 Section 1 : Algebra Q1. Let G be a group of order n. Which of the following conditions imply that G is abelian?

NBHM QUESTION 2007 Section 1 : Algebra Q1. Let G be a group of order n. Which of the following conditions imply that G is abelian? NBHM QUESTION 7 NBHM QUESTION 7 NBHM QUESTION 7 Sectio : Algebra Q Let G be a group of order Which of the followig coditios imply that G is abelia? 5 36 Q Which of the followig subgroups are ecesarily

More information

Proposition 2.1. There are an infinite number of primes of the form p = 4n 1. Proof. Suppose there are only a finite number of such primes, say

Proposition 2.1. There are an infinite number of primes of the form p = 4n 1. Proof. Suppose there are only a finite number of such primes, say Chater 2 Euclid s Theorem Theorem 2.. There are a ifiity of rimes. This is sometimes called Euclid s Secod Theorem, what we have called Euclid s Lemma beig kow as Euclid s First Theorem. Proof. Suose to

More information

MATH 10550, EXAM 3 SOLUTIONS

MATH 10550, EXAM 3 SOLUTIONS MATH 155, EXAM 3 SOLUTIONS 1. I fidig a approximate solutio to the equatio x 3 +x 4 = usig Newto s method with iitial approximatio x 1 = 1, what is x? Solutio. Recall that x +1 = x f(x ) f (x ). Hece,

More information

Chapter 3 Inner Product Spaces. Hilbert Spaces

Chapter 3 Inner Product Spaces. Hilbert Spaces Chapter 3 Ier Product Spaces. Hilbert Spaces 3. Ier Product Spaces. Hilbert Spaces 3.- Defiitio. A ier product space is a vector space X with a ier product defied o X. A Hilbert space is a complete ier

More information

A) is empty. B) is a finite set. C) can be a countably infinite set. D) can be an uncountable set.

A) is empty. B) is a finite set. C) can be a countably infinite set. D) can be an uncountable set. M.A./M.Sc. (Mathematics) Etrace Examiatio 016-17 Max Time: hours Max Marks: 150 Istructios: There are 50 questios. Every questio has four choices of which exactly oe is correct. For correct aswer, 3 marks

More information

Fundamental Concepts: Surfaces and Curves

Fundamental Concepts: Surfaces and Curves UNDAMENTAL CONCEPTS: SURACES AND CURVES CHAPTER udametal Cocepts: Surfaces ad Curves. INTRODUCTION This chapter describes two geometrical objects, vi., surfaces ad curves because the pla a ver importat

More information

If a subset E of R contains no open interval, is it of zero measure? For instance, is the set of irrationals in [0, 1] is of measure zero?

If a subset E of R contains no open interval, is it of zero measure? For instance, is the set of irrationals in [0, 1] is of measure zero? 2 Lebesgue Measure I Chapter 1 we defied the cocept of a set of measure zero, ad we have observed that every coutable set is of measure zero. Here are some atural questios: If a subset E of R cotais a

More information

Singular value decomposition. Mathématiques appliquées (MATH0504-1) B. Dewals, Ch. Geuzaine

Singular value decomposition. Mathématiques appliquées (MATH0504-1) B. Dewals, Ch. Geuzaine Lecture 11 Sigular value decompositio Mathématiques appliquées (MATH0504-1) B. Dewals, Ch. Geuzaie V1.2 07/12/2018 1 Sigular value decompositio (SVD) at a glace Motivatio: the image of the uit sphere S

More information

1 1 2 = show that: over variables x and y. [2 marks] Write down necessary conditions involving first and second-order partial derivatives for ( x0, y

1 1 2 = show that: over variables x and y. [2 marks] Write down necessary conditions involving first and second-order partial derivatives for ( x0, y Questio (a) A square matrix A= A is called positive defiite if the quadratic form waw > 0 for every o-zero vector w [Note: Here (.) deotes the traspose of a matrix or a vector]. Let 0 A = 0 = show that:

More information

Physics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001.

Physics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001. Physics 324, Fall 2002 Dirac Notatio These otes were produced by David Kapla for Phys. 324 i Autum 2001. 1 Vectors 1.1 Ier product Recall from liear algebra: we ca represet a vector V as a colum vector;

More information

Eigenvalues and Eigenvectors

Eigenvalues and Eigenvectors 5 Eigevalues ad Eigevectors 5.3 DIAGONALIZATION DIAGONALIZATION Example 1: Let. Fid a formula for A k, give that P 1 1 = 1 2 ad, where Solutio: The stadard formula for the iverse of a 2 2 matrix yields

More information

PUTNAM TRAINING PROBABILITY

PUTNAM TRAINING PROBABILITY PUTNAM TRAINING PROBABILITY (Last udated: December, 207) Remark. This is a list of exercises o robability. Miguel A. Lerma Exercises. Prove that the umber of subsets of {, 2,..., } with odd cardiality

More information

[ 11 ] z of degree 2 as both degree 2 each. The degree of a polynomial in n variables is the maximum of the degrees of its terms.

[ 11 ] z of degree 2 as both degree 2 each. The degree of a polynomial in n variables is the maximum of the degrees of its terms. [ 11 ] 1 1.1 Polyomial Fuctios 1 Algebra Ay fuctio f ( x) ax a1x... a1x a0 is a polyomial fuctio if ai ( i 0,1,,,..., ) is a costat which belogs to the set of real umbers ad the idices,, 1,...,1 are atural

More information

Lecture 7: Properties of Random Samples

Lecture 7: Properties of Random Samples Lecture 7: Properties of Radom Samples 1 Cotiued From Last Class Theorem 1.1. Let X 1, X,...X be a radom sample from a populatio with mea µ ad variace σ

More information

YALE UNIVERSITY DEPARTMENT OF COMPUTER SCIENCE

YALE UNIVERSITY DEPARTMENT OF COMPUTER SCIENCE YALE UNIVERSITY DEPARTMENT OF COMPUTER SCIENCE CPSC 467a: Crytograhy ad Comuter Security Notes 16 (rev. 1 Professor M. J. Fischer November 3, 2008 68 Legedre Symbol Lecture Notes 16 ( Let be a odd rime,

More information

Decoupling seminar notes

Decoupling seminar notes Decoulig semiar otes I the last two lectures, we discuss the roof of the l 2 -decoulig cojecture I thought it would be helful to have some otes to look over betwee the two lectures There are some exercises

More information

Real Numbers R ) - LUB(B) may or may not belong to B. (Ex; B= { y: y = 1 x, - Note that A B LUB( A) LUB( B)

Real Numbers R ) - LUB(B) may or may not belong to B. (Ex; B= { y: y = 1 x, - Note that A B LUB( A) LUB( B) Real Numbers The least upper boud - Let B be ay subset of R B is bouded above if there is a k R such that x k for all x B - A real umber, k R is a uique least upper boud of B, ie k = LUB(B), if () k is

More information

MAS111 Convergence and Continuity

MAS111 Convergence and Continuity MAS Covergece ad Cotiuity Key Objectives At the ed of the course, studets should kow the followig topics ad be able to apply the basic priciples ad theorems therei to solvig various problems cocerig covergece

More information

1 Last time: similar and diagonalizable matrices

1 Last time: similar and diagonalizable matrices Last time: similar ad diagoalizable matrices Let be a positive iteger Suppose A is a matrix, v R, ad λ R Recall that v a eigevector for A with eigevalue λ if v ad Av λv, or equivaletly if v is a ozero

More information

Weil Conjecture I. Yichao Tian. Morningside Center of Mathematics, AMSS, CAS

Weil Conjecture I. Yichao Tian. Morningside Center of Mathematics, AMSS, CAS Weil Cojecture I Yichao Tia Morigside Ceter of Mathematics, AMSS, CAS [This is the sketch of otes of the lecture Weil Cojecture I give by Yichao Tia at MSC, Tsighua Uiversity, o August 4th, 20. Yuaqig

More information

6. Kalman filter implementation for linear algebraic equations. Karhunen-Loeve decomposition

6. Kalman filter implementation for linear algebraic equations. Karhunen-Loeve decomposition 6. Kalma filter implemetatio for liear algebraic equatios. Karhue-Loeve decompositio 6.1. Solvable liear algebraic systems. Probabilistic iterpretatio. Let A be a quadratic matrix (ot obligatory osigular.

More information

PRELIM PROBLEM SOLUTIONS

PRELIM PROBLEM SOLUTIONS PRELIM PROBLEM SOLUTIONS THE GRAD STUDENTS + KEN Cotets. Complex Aalysis Practice Problems 2. 2. Real Aalysis Practice Problems 2. 4 3. Algebra Practice Problems 2. 8. Complex Aalysis Practice Problems

More information

Teresa Formisano. A thesis submitted in fulfillment of the Degree of Doctor of. Philosophy of London Metropolitan University

Teresa Formisano. A thesis submitted in fulfillment of the Degree of Doctor of. Philosophy of London Metropolitan University Miimax i the theory of oerators o Hilbert saces ad Clarkso-McCarthy estimates for l q S ) saces of oerators i Schatte ideals Teresa Formisao A thesis submitted i fulfillmet of the Degree of Doctor of Philosohy

More information

On Cesáro means for Fox-Wright functions

On Cesáro means for Fox-Wright functions Joural of Mathematics ad Statistics: 4(3: 56-6, 8 ISSN: 549-3644 8 Sciece Publicatios O Cesáro meas for Fox-Wright fuctios Maslia Darus ad Rabha W. Ibrahim School of Mathematical Scieces, Faculty of Sciece

More information

3.2 Properties of Division 3.3 Zeros of Polynomials 3.4 Complex and Rational Zeros of Polynomials

3.2 Properties of Division 3.3 Zeros of Polynomials 3.4 Complex and Rational Zeros of Polynomials Math 60 www.timetodare.com 3. Properties of Divisio 3.3 Zeros of Polyomials 3.4 Complex ad Ratioal Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered

More information

Lesson 10: Limits and Continuity

Lesson 10: Limits and Continuity www.scimsacademy.com Lesso 10: Limits ad Cotiuity SCIMS Academy 1 Limit of a fuctio The cocept of limit of a fuctio is cetral to all other cocepts i calculus (like cotiuity, derivative, defiite itegrals

More information

Math 61CM - Solutions to homework 3

Math 61CM - Solutions to homework 3 Math 6CM - Solutios to homework 3 Cédric De Groote October 2 th, 208 Problem : Let F be a field, m 0 a fixed oegative iteger ad let V = {a 0 + a x + + a m x m a 0,, a m F} be the vector space cosistig

More information

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row:

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row: Math 5-4 Tue Feb 4 Cotiue with sectio 36 Determiats The effective way to compute determiats for larger-sized matrices without lots of zeroes is to ot use the defiitio, but rather to use the followig facts,

More information

PRIME RECIPROCALS AND PRIMES IN ARITHMETIC PROGRESSION

PRIME RECIPROCALS AND PRIMES IN ARITHMETIC PROGRESSION PRIME RECIPROCALS AND PRIMES IN ARITHMETIC PROGRESSION DANIEL LITT Abstract. This aer is a exository accout of some (very elemetary) argumets o sums of rime recirocals; though the statemets i Proositios

More information

The Method of Least Squares. To understand least squares fitting of data.

The Method of Least Squares. To understand least squares fitting of data. The Method of Least Squares KEY WORDS Curve fittig, least square GOAL To uderstad least squares fittig of data To uderstad the least squares solutio of icosistet systems of liear equatios 1 Motivatio Curve

More information

8. Applications To Linear Differential Equations

8. Applications To Linear Differential Equations 8. Applicatios To Liear Differetial Equatios 8.. Itroductio 8.. Review Of Results Cocerig Liear Differetial Equatios Of First Ad Secod Orders 8.3. Eercises 8.4. Liear Differetial Equatios Of Order N 8.5.

More information

An operator equality involving a continuous field of operators and its norm inequalities

An operator equality involving a continuous field of operators and its norm inequalities Available olie at www.sciecedirect.com Liear Algebra ad its Alicatios 49 (008) 59 67 www.elsevier.com/locate/laa A oerator equality ivolvig a cotiuous field of oerators ad its orm iequalities Mohammad

More information

MTH Assignment 1 : Real Numbers, Sequences

MTH Assignment 1 : Real Numbers, Sequences MTH -26 Assigmet : Real Numbers, Sequeces. Fid the supremum of the set { m m+ : N, m Z}. 2. Let A be a o-empty subset of R ad α R. Show that α = supa if ad oly if α is ot a upper boud of A but α + is a

More information

Lecture 8: October 20, Applications of SVD: least squares approximation

Lecture 8: October 20, Applications of SVD: least squares approximation Mathematical Toolkit Autum 2016 Lecturer: Madhur Tulsiai Lecture 8: October 20, 2016 1 Applicatios of SVD: least squares approximatio We discuss aother applicatio of sigular value decompositio (SVD) of

More information

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a Math E-2b Lecture #8 Notes This week is all about determiats. We ll discuss how to defie them, how to calculate them, lear the allimportat property kow as multiliearity, ad show that a square matrix A

More information

Notes for Lecture 11

Notes for Lecture 11 U.C. Berkeley CS78: Computatioal Complexity Hadout N Professor Luca Trevisa 3/4/008 Notes for Lecture Eigevalues, Expasio, ad Radom Walks As usual by ow, let G = (V, E) be a udirected d-regular graph with

More information

ON SOME NEW SEQUENCE SPACES OF NON-ABSOLUTE TYPE RELATED TO THE SPACES l p AND l I. M. Mursaleen and Abdullah K. Noman

ON SOME NEW SEQUENCE SPACES OF NON-ABSOLUTE TYPE RELATED TO THE SPACES l p AND l I. M. Mursaleen and Abdullah K. Noman Faculty of Scieces ad Mathematics, Uiversity of Niš, Serbia Available at: htt://www.mf.i.ac.rs/filomat Filomat 25:2 20, 33 5 DOI: 0.2298/FIL02033M ON SOME NEW SEQUENCE SPACES OF NON-ABSOLUTE TYPE RELATED

More information

Chapter 1. Complex Numbers. Dr. Pulak Sahoo

Chapter 1. Complex Numbers. Dr. Pulak Sahoo Chapter 1 Complex Numbers BY Dr. Pulak Sahoo Assistat Professor Departmet of Mathematics Uiversity Of Kalyai West Begal, Idia E-mail : sahoopulak1@gmail.com 1 Module-2: Stereographic Projectio 1 Euler

More information

Notes on the prime number theorem

Notes on the prime number theorem Notes o the rime umber theorem Keji Kozai May 2, 24 Statemet We begi with a defiitio. Defiitio.. We say that f(x) ad g(x) are asymtotic as x, writte f g, if lim x f(x) g(x) =. The rime umber theorem tells

More information

Ma 4121: Introduction to Lebesgue Integration Solutions to Homework Assignment 5

Ma 4121: Introduction to Lebesgue Integration Solutions to Homework Assignment 5 Ma 42: Itroductio to Lebesgue Itegratio Solutios to Homework Assigmet 5 Prof. Wickerhauser Due Thursday, April th, 23 Please retur your solutios to the istructor by the ed of class o the due date. You

More information

PERIODS OF FIBONACCI SEQUENCES MODULO m. 1. Preliminaries Definition 1. A generalized Fibonacci sequence is an infinite complex sequence (g n ) n Z

PERIODS OF FIBONACCI SEQUENCES MODULO m. 1. Preliminaries Definition 1. A generalized Fibonacci sequence is an infinite complex sequence (g n ) n Z PERIODS OF FIBONACCI SEQUENCES MODULO m ARUDRA BURRA Abstract. We show that the Fiboacci sequece modulo m eriodic for all m, ad study the eriod i terms of the modulus.. Prelimiaries Defiitio. A geeralized

More information

Maths /2014. CCP Maths 2. Reduction, projector,endomorphism of rank 1... Hadamard s inequality and some applications. Solution.

Maths /2014. CCP Maths 2. Reduction, projector,endomorphism of rank 1... Hadamard s inequality and some applications. Solution. CCP Maths 2 Reductio, projector,edomorphism of rak 1... Hadamard s iequality ad some applicatios Solutio Exercise 1. 1 A is a symmetric matrix so diagoalizable. 2 Diagoalizatio of A : A characteristic

More information

b i u x i U a i j u x i u x j

b i u x i U a i j u x i u x j M ath 5 2 7 Fall 2 0 0 9 L ecture 1 9 N ov. 1 6, 2 0 0 9 ) S ecod- Order Elliptic Equatios: Weak S olutios 1. Defiitios. I this ad the followig two lectures we will study the boudary value problem Here

More information

Theorem: Let A n n. In this case that A does reduce to I, we search for A 1 as the solution matrix X to the matrix equation A X = I i.e.

Theorem: Let A n n. In this case that A does reduce to I, we search for A 1 as the solution matrix X to the matrix equation A X = I i.e. Theorem: Let A be a square matrix The A has a iverse matrix if ad oly if its reduced row echelo form is the idetity I this case the algorithm illustrated o the previous page will always yield the iverse

More information

PROBLEM SET 5 SOLUTIONS. Solution. We prove that the given congruence equation has no solutions. Suppose for contradiction that. (x 2) 2 1 (mod 7).

PROBLEM SET 5 SOLUTIONS. Solution. We prove that the given congruence equation has no solutions. Suppose for contradiction that. (x 2) 2 1 (mod 7). PROBLEM SET 5 SOLUTIONS 1 Fid every iteger solutio to x 17x 5 0 mod 45 Solutio We rove that the give cogruece equatio has o solutios Suose for cotradictio that the equatio x 17x 5 0 mod 45 has a solutio

More information

Iterative Techniques for Solving Ax b -(3.8). Assume that the system has a unique solution. Let x be the solution. Then x A 1 b.

Iterative Techniques for Solving Ax b -(3.8). Assume that the system has a unique solution. Let x be the solution. Then x A 1 b. Iterative Techiques for Solvig Ax b -(8) Cosider solvig liear systems of them form: Ax b where A a ij, x x i, b b i Assume that the system has a uique solutio Let x be the solutio The x A b Jacobi ad Gauss-Seidel

More information

24 MATH 101B: ALGEBRA II, PART D: REPRESENTATIONS OF GROUPS

24 MATH 101B: ALGEBRA II, PART D: REPRESENTATIONS OF GROUPS 24 MATH 101B: ALGEBRA II, PART D: REPRESENTATIONS OF GROUPS Corollary 2.30. Suppose that the semisimple decompositio of the G- module V is V = i S i. The i = χ V,χ i Proof. Sice χ V W = χ V + χ W, we have:

More information

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer.

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer. 6 Itegers Modulo I Example 2.3(e), we have defied the cogruece of two itegers a,b with respect to a modulus. Let us recall that a b (mod ) meas a b. We have proved that cogruece is a equivalece relatio

More information

1 lim. f(x) sin(nx)dx = 0. n sin(nx)dx

1 lim. f(x) sin(nx)dx = 0. n sin(nx)dx Problem A. Calculate ta(.) to 4 decimal places. Solutio: The power series for si(x)/ cos(x) is x + x 3 /3 + (2/5)x 5 +. Puttig x =. gives ta(.) =.3. Problem 2A. Let f : R R be a cotiuous fuctio. Show that

More information

Continuous Functions

Continuous Functions Cotiuous Fuctios Q What does it mea for a fuctio to be cotiuous at a poit? Aswer- I mathematics, we have a defiitio that cosists of three cocepts that are liked i a special way Cosider the followig defiitio

More information

Solutions to Problem Set 7

Solutions to Problem Set 7 8.78 Solutios to Problem Set 7. If the umber is i S, we re doe sice it s relatively rime to everythig. So suose S. Break u the remaiig elemets ito airs {, }, {4, 5},..., {, + }. By the Pigeohole Pricile,

More information

x x x Using a second Taylor polynomial with remainder, find the best constant C so that for x 0,

x x x Using a second Taylor polynomial with remainder, find the best constant C so that for x 0, Math Activity 9( Due with Fial Eam) Usig first ad secod Taylor polyomials with remaider, show that for, 8 Usig a secod Taylor polyomial with remaider, fid the best costat C so that for, C 9 The th Derivative

More information

Sequences and Series of Functions

Sequences and Series of Functions Chapter 6 Sequeces ad Series of Fuctios 6.1. Covergece of a Sequece of Fuctios Poitwise Covergece. Defiitio 6.1. Let, for each N, fuctio f : A R be defied. If, for each x A, the sequece (f (x)) coverges

More information

Machine Learning for Data Science (CS 4786)

Machine Learning for Data Science (CS 4786) Machie Learig for Data Sciece CS 4786) Lecture & 3: Pricipal Compoet Aalysis The text i black outlies high level ideas. The text i blue provides simple mathematical details to derive or get to the algorithm

More information

Math 143 Review for Quiz 14 page 1

Math 143 Review for Quiz 14 page 1 Math Review for Quiz age. Solve each of the followig iequalities. x + a) < x + x c) x d) x x +

More information

Seunghee Ye Ma 8: Week 5 Oct 28

Seunghee Ye Ma 8: Week 5 Oct 28 Week 5 Summary I Sectio, we go over the Mea Value Theorem ad its applicatios. I Sectio 2, we will recap what we have covered so far this term. Topics Page Mea Value Theorem. Applicatios of the Mea Value

More information

SUPPLEMENT TO GEOMETRIC INFERENCE FOR GENERAL HIGH-DIMENSIONAL LINEAR INVERSE PROBLEMS

SUPPLEMENT TO GEOMETRIC INFERENCE FOR GENERAL HIGH-DIMENSIONAL LINEAR INVERSE PROBLEMS Submitted to the Aals of Statistics arxiv: arxiv:0000.0000 SUPPLEMENT TO GEOMETRIC INFERENCE FOR GENERAL HIGH-DIMENSIONAL LINEAR INVERSE PROBLEMS By T. Toy Cai, Tegyua Liag ad Alexader Rakhli The Wharto

More information

1. C only. 3. none of them. 4. B only. 5. B and C. 6. all of them. 7. A and C. 8. A and B correct

1. C only. 3. none of them. 4. B only. 5. B and C. 6. all of them. 7. A and C. 8. A and B correct M408D (54690/54695/54700), Midterm # Solutios Note: Solutios to the multile-choice questios for each sectio are listed below. Due to radomizatio betwee sectios, exlaatios to a versio of each of the multile-choice

More information

arxiv: v1 [math.dg] 27 Jul 2012

arxiv: v1 [math.dg] 27 Jul 2012 ESTIMATES FOR EIGENVALUES OF THE PANEITZ OPERATOR* arxiv:107.650v1 [math.dg] 7 Jul 01 QING-MING CHENG Abstract. For a -dimesioal compact submaifold i the Euclidea space R N, we study estimates for eigevalues

More information

Assignment 1 : Real Numbers, Sequences. for n 1. Show that (x n ) converges. Further, by observing that x n+2 + x n+1

Assignment 1 : Real Numbers, Sequences. for n 1. Show that (x n ) converges. Further, by observing that x n+2 + x n+1 Assigmet : Real Numbers, Sequeces. Let A be a o-empty subset of R ad α R. Show that α = supa if ad oly if α is ot a upper boud of A but α + is a upper boud of A for every N. 2. Let y (, ) ad x (, ). Evaluate

More information

THE ASYMPTOTIC COMPLEXITY OF MATRIX REDUCTION OVER FINITE FIELDS

THE ASYMPTOTIC COMPLEXITY OF MATRIX REDUCTION OVER FINITE FIELDS THE ASYMPTOTIC COMPLEXITY OF MATRIX REDUCTION OVER FINITE FIELDS DEMETRES CHRISTOFIDES Abstract. Cosider a ivertible matrix over some field. The Gauss-Jorda elimiatio reduces this matrix to the idetity

More information

13.1 Shannon lower bound

13.1 Shannon lower bound ECE598: Iformatio-theoretic methods i high-dimesioal statistics Srig 016 Lecture 13: Shao lower boud, Fao s method Lecturer: Yihog Wu Scribe: Daewo Seo, Mar 8, 016 [Ed Mar 11] I the last class, we leared

More information

TMA4205 Numerical Linear Algebra. The Poisson problem in R 2 : diagonalization methods

TMA4205 Numerical Linear Algebra. The Poisson problem in R 2 : diagonalization methods TMA4205 Numerical Liear Algebra The Poisso problem i R 2 : diagoalizatio methods September 3, 2007 c Eiar M Røquist Departmet of Mathematical Scieces NTNU, N-749 Trodheim, Norway All rights reserved A

More information

Functional Analysis: Assignment Set # 10 Spring Professor: Fengbo Hang April 22, 2009

Functional Analysis: Assignment Set # 10 Spring Professor: Fengbo Hang April 22, 2009 Eduardo Coroa Fuctioal Aalysis: Assigmet Set # 0 Srig 2009 Professor: Fegbo Hag Aril 22, 2009 Theorem Let S be a comact Hausdor sace. Suose fgg is a collectio of comlex-valued fuctios o S satisfyig (i)

More information

Linear regression. Daniel Hsu (COMS 4771) (y i x T i β)2 2πσ. 2 2σ 2. 1 n. (x T i β y i ) 2. 1 ˆβ arg min. β R n d

Linear regression. Daniel Hsu (COMS 4771) (y i x T i β)2 2πσ. 2 2σ 2. 1 n. (x T i β y i ) 2. 1 ˆβ arg min. β R n d Liear regressio Daiel Hsu (COMS 477) Maximum likelihood estimatio Oe of the simplest liear regressio models is the followig: (X, Y ),..., (X, Y ), (X, Y ) are iid radom pairs takig values i R d R, ad Y

More information

An Application of Generalized Bessel Functions on Certain Subclasses of Analytic Functions

An Application of Generalized Bessel Functions on Certain Subclasses of Analytic Functions Turkish Joural of Aalysis ad Nuber Theory, 5, Vol 3, No, -6 Available olie at htt://ubsscieubco/tjat/3// Sciece ad Educatio ublishig DOI:69/tjat-3-- A Alicatio of Geeralized Bessel Fuctios o Certai Subclasses

More information

Modern Algebra. Previous year Questions from 2017 to Ramanasri

Modern Algebra. Previous year Questions from 2017 to Ramanasri Moder Algebra Previous year Questios from 017 to 199 Ramaasri 017 S H O P NO- 4, 1 S T F L O O R, N E A R R A P I D F L O U R M I L L S, O L D R A J E N D E R N A G A R, N E W D E L H I. W E B S I T E

More information

Week 5-6: The Binomial Coefficients

Week 5-6: The Binomial Coefficients Wee 5-6: The Biomial Coefficiets March 6, 2018 1 Pascal Formula Theorem 11 (Pascal s Formula For itegers ad such that 1, ( ( ( 1 1 + 1 The umbers ( 2 ( 1 2 ( 2 are triagle umbers, that is, The petago umbers

More information

Chimica Inorganica 3

Chimica Inorganica 3 himica Iorgaica Irreducible Represetatios ad haracter Tables Rather tha usig geometrical operatios, it is ofte much more coveiet to employ a ew set of group elemets which are matrices ad to make the rule

More information

Solutions to Problem Sheet 1

Solutions to Problem Sheet 1 Solutios to Problem Sheet ) Use Theorem. to rove that loglog for all real 3. This is a versio of Theorem. with the iteger N relaced by the real. Hit Give 3 let N = [], the largest iteger. The, imortatly,

More information

AH Checklist (Unit 3) AH Checklist (Unit 3) Matrices

AH Checklist (Unit 3) AH Checklist (Unit 3) Matrices AH Checklist (Uit 3) AH Checklist (Uit 3) Matrices Skill Achieved? Kow that a matrix is a rectagular array of umbers (aka etries or elemets) i paretheses, each etry beig i a particular row ad colum Kow

More information