Alexander Ostrowski

Size: px
Start display at page:

Download "Alexander Ostrowski"

Transcription

1 Ostrowski p. 1/3 Alexander Ostrowski Walter Gautschi Purdue University

2 Ostrowski p. 2/3 Collected Mathematical Papers Volume 1 Determinants Linear Algebra Algebraic Equations

3 Ostrowski p. 2/3 Collected Mathematical Papers Volume 1 Determinants Linear Algebra Algebraic Equations Volume 2 Multivariate Algebra Formal Algebra

4 Ostrowski p. 2/3 Collected Mathematical Papers Volume 1 Determinants Linear Algebra Algebraic Equations Volume 2 Multivariate Algebra Formal Algebra Volume 3 Number Theory Geometry Topology Convergence

5 Ostrowski p. 3/3 Collected Mathematical Papers Volume 4 Real Function Theory Differential Equations Differential Transformations (continued)

6 Ostrowski p. 3/3 Collected Mathematical Papers Volume 4 Real Function Theory Differential Equations Differential Transformations Volume 5 Complex Function Theory (continued)

7 Ostrowski p. 3/3 Collected Mathematical Papers Volume 4 Real Function Theory Differential Equations Differential Transformations Volume 5 Complex Function Theory Volume 6 Conformal Mapping Numerical Analysis Miscellaneous (continued)

8 Ostrowski p. 4/3 Ostrowski s mother Ostrowski, the cadett

9 Ostrowski p. 5/3 Vol.1. Determinants, Linear Algebra, Algebraic Equations Determinants and Linear Algebra (1937) Matrices with dominant diagonal A = [a ij ], d i := a ii j i a ij > 0, all i Hadamard (1899): det A 0 Ostrowski: det A i d i

10 Vol.1. Determinants, Linear Algebra, Algebraic Equations Determinants and Linear Algebra (1937) Matrices with dominant diagonal A = [a ij ], d i := a ii j i a ij > 0, all i Hadamard (1899): det A 0 Ostrowski: det A i d i (1937) M-matrices A = [a ij ], a ii > 0, a ij 0 (i j) a a 11 > 0, 11 a 12 a 21 a 22 > 0,..., det A > 0 Ostrowski p. 5/3

11 Ostrowski p. 6/3 Vol.1 (continued) Thm. If A is an M-matrix, then A 1 0 (1955) General theory of vector and matrix norms ( ) Rayleigh quotient iteration for computing real eigenvalues of a matrix A for k = 0, 1, 2,... do ρ 0 = 0, x 1 arbitrary (A ρ k I)x k = x k 1, ρ k+1 = x T k Ax k/x T k x k Convergence ρ k λ to an eigenvalue λ of A is cubic if A T = A and quadratic otherwise (in general). Generalized Rayleigh quotient iteration (involving bilinear forms) always converges cubically. ( ) Positive matrices (Frobenius theory)

12 David Hilbert Ostrowski p. 7/3

13 Ostrowski p. 8/3 Algebraic Equations (1933) Critique and correction of Gauss s first and fourth proof of the Fundamental Theorem of Algebra (1939) Continuity of the roots of an algebraic equation as a function of the coefficients: quantitative statement

14 Algebraic Equations (1933) Critique and correction of Gauss s first and fourth proof of the Fundamental Theorem of Algebra (1939) Continuity of the roots of an algebraic equation as a function of the coefficients: quantitative statement Theorem Let x ν, y ν be the zeros of resp. p(z) = a 0 z n + a 1 z n a n, a 0 a n 0 q(z) = b 0 z n + b 1 z n b n, b 0 b n 0. If b ν a ν = ε ν a ν, ε ν ε, 16nε 1/n 1, then, with x ν and y ν suitably ordered, x ν y ν x ν 15nε1/n. Ostrowski p. 8/3

15 Ostrowski p. 9/3 Algebraic Equations (continued) (1940) Long memoir on Graeffe s method ( ) Sign rules (Descartes, Budan-Fourier, Runge) (1979!) A little mathematical jewel

16 Ostrowski p. 9/3 Algebraic Equations (continued) (1940) Long memoir on Graeffe s method ( ) Sign rules (Descartes, Budan-Fourier, Runge) (1979!) A little mathematical jewel Theorem Let p and q be polynomials of degrees m and n, respectively. Define Then M f = max z =1 f(z). γm p M q M pq M p M q, γ = sin m π 8m sinn π 8n.

17 Ostrowski, the skater Ostrowski p. 10/3

18 Ostrowski p. 11/3 Vol. 2. Multivariate Algebra, Formal Algebra Multivariate Algebra ( ) Existence of a finite basis B for a system S of polynomials in several variables. Example: necessary and sufficient conditions for S = {x α 1,i 1 x α 2,i 2 x α n,i n : α ν,i N 0, i = 1, 2, 3,... }

19 Ostrowski p. 11/3 Vol. 2. Multivariate Algebra, Formal Algebra Multivariate Algebra ( ) Existence of a finite basis B for a system S of polynomials in several variables. Example: necessary and sufficient conditions for S = {x α 1,i 1 x α 2,i 2 x α n,i n : α ν,i N 0, i = 1, 2, 3,... } (1924) Theory of invariants of binary forms of degree n

20 Ostrowski p. 11/3 Vol. 2. Multivariate Algebra, Formal Algebra Multivariate Algebra ( ) Existence of a finite basis B for a system S of polynomials in several variables. Example: necessary and sufficient conditions for S = {x α 1,i 1 x α 2,i 2 x α n,i n : α ν,i N 0, i = 1, 2, 3,... } (1924) Theory of invariants of binary forms of degree n (1922, ) Various questions of irreducibility

21 Ostrowski p. 11/3 Vol. 2. Multivariate Algebra, Formal Algebra Multivariate Algebra ( ) Existence of a finite basis B for a system S of polynomials in several variables. Example: necessary and sufficient conditions for S = {x α 1,i 1 x α 2,i 2 x α n,i n : α ν,i N 0, i = 1, 2, 3,... } (1924) Theory of invariants of binary forms of degree n (1922, ) Various questions of irreducibility Formal Algebra (1913!) Algebra of finite fields (37-page memoir in Ukrainian)

22 Ostrowski p. 12/3 Formal Algebra (continued) ( ) Theory of valuation on a field. (Generalizing the concept of absolute value in the field of real numbers to general fields.) Perfect fields and extensions thereof

23 Ostrowski p. 12/3 Formal Algebra (continued) ( ) Theory of valuation on a field. (Generalizing the concept of absolute value in the field of real numbers to general fields.) Perfect fields and extensions thereof (1934) Arithmetic theory of fields (1936) Structure of polynomial rings

24 Ostrowski p. 12/3 Formal Algebra (continued) ( ) Theory of valuation on a field. (Generalizing the concept of absolute value in the field of real numbers to general fields.) Perfect fields and extensions thereof (1934) Arithmetic theory of fields (1936) Structure of polynomial rings (1954) Evaluation of polynomials p n (x) = a 0 x n + a 1 x n a n 1 x + a n by Horner s rule p 0 = a 0, p ν = xp ν 1 + a ν, ν = 1, 2,..., n Complexity: n additions, n multiplications. Optimal for addition, optimal for multiplication when n 4.

25 Formal Algebra (continued) The year 1954 is generally considered the year of birth of algebraic complexity theory (P. Bürgisser and M. Clausen, 1996). (1961) Metric properties of block matrices A = A 11 A 12 A 1n A 21 A 22 A 2n.. A n1 A n2 A nn., A νµ R ν µ, det A νν 0 Example: Is Hadamard s theorem still valid if is replaced by? Answer: yes, if the associated matrix is an M-matrix, where A 11 A 12 A 1n A 21 A 22 A 2n.. A n1 A n2 A nn B = min x =1 Bx,. B = max x =1 Bx Ostrowski p. 13/3

26 Ostrowski p. 14/3 Formal Algebra (continued) (1961) Convergence of block iterative methods for solving Ax = b, where A is a block matrix

27 Ostrowski p. 14/3 Formal Algebra (continued) (1961) Convergence of block iterative methods for solving Ax = b, where A is a block matrix (1977) Kronecker s elimination theory in the general setting of polynomial ideals

28 Ostrowski in his 40s Ostrowski p. 15/3

29 Ostrowski p. 16/3 Vol. 3. Number Theory, Geometry, Topology, Convergence Number Theory (1919) Polynomials with coefficients in a finite arithmetic field taking on integer values for integer arguments. Existence of a regular basis

30 Ostrowski p. 16/3 Vol. 3. Number Theory, Geometry, Topology, Convergence Number Theory (1919) Polynomials with coefficients in a finite arithmetic field taking on integer values for integer arguments. Existence of a regular basis (1919) Arithmetic theory of algebraic numbers

31 Ostrowski p. 16/3 Vol. 3. Number Theory, Geometry, Topology, Convergence Number Theory (1919) Polynomials with coefficients in a finite arithmetic field taking on integer values for integer arguments. Existence of a regular basis (1919) Arithmetic theory of algebraic numbers ( , ) Diophantine equations and approximations

32 Ostrowski p. 17/3 Geometry (1955) A study of evolutes and evolvents of a plane curve (under weak differentiability assumptions). Application to ovals

33 Ostrowski p. 17/3 Geometry (1955) A study of evolutes and evolvents of a plane curve (under weak differentiability assumptions). Application to ovals (1955) Differential geometry of plane parallel curves

34 Ostrowski p. 17/3 Geometry (1955) A study of evolutes and evolvents of a plane curve (under weak differentiability assumptions). Application to ovals (1955) Differential geometry of plane parallel curves (1956) Necessary and sufficient conditions for two line elements to be connectable by a curve along which the curvature is monotone

35 Ostrowski p. 17/3 Geometry (1955) A study of evolutes and evolvents of a plane curve (under weak differentiability assumptions). Application to ovals (1955) Differential geometry of plane parallel curves (1956) Necessary and sufficient conditions for two line elements to be connectable by a curve along which the curvature is monotone Topology (1933) Existence criterion for a common zero of two real functions continuous inside and on the boundary of a disk

36 Ostrowski p. 17/3 Geometry (1955) A study of evolutes and evolvents of a plane curve (under weak differentiability assumptions). Application to ovals (1955) Differential geometry of plane parallel curves (1956) Necessary and sufficient conditions for two line elements to be connectable by a curve along which the curvature is monotone Topology (1933) Existence criterion for a common zero of two real functions continuous inside and on the boundary of a disk (1935) Topology of oriented line elements

37 Ostrowski in his 50s Ostrowski p. 18/3

38 Ostrowski p. 19/3 Convergence (1930) Infinite products (1 + x ν ) = Φ(x) where x 0 = x, x ν+1 = ϕ(x ν ), ν = 0, 1, 2,... ν=0 Example: Euler s product ϕ(x) = x 2, Φ(x) = (1 x) 1. Problem: find all products which converge in a neighborhood of x = 0, and for which ϕ is rational and Φ algebraic.

39 Ostrowski p. 19/3 Convergence (1930) Infinite products (1 + x ν ) = Φ(x) where x 0 = x, x ν+1 = ϕ(x ν ), ν = 0, 1, 2,... ν=0 Example: Euler s product ϕ(x) = x 2, Φ(x) = (1 x) 1. Problem: find all products which converge in a neighborhood of x = 0, and for which ϕ is rational and Φ algebraic. (1930) Normal power series: a ν z ν with a ν 0, a 2 ν a ν 1 a ν+1 ν= and all coefficients between two positive ones are also positive. Theorem: The product of two normal power series is also normal.

40 Ostrowski p. 20/3 Convergence (continued) (1955) Convergence and divergence criteria of Ermakov for f(x)dx

41 Ostrowski p. 20/3 Convergence (continued) (1955) Convergence and divergence criteria of Ermakov for f(x)dx (1956) Fixed point iteration x ν+1 = f(x ν ), ν = 0, 1, 2,..., where f(x) I if x I. Behavior of {x ν } in case of divergence

42 Ostrowski p. 20/3 Convergence (continued) (1955) Convergence and divergence criteria of Ermakov for f(x)dx (1956) Fixed point iteration x ν+1 = f(x ν ), ν = 0, 1, 2,..., where f(x) I if x I. Behavior of {x ν } in case of divergence (1972) Summation of slowly convergent positive or alternating series

43 Ostrowski p. 21/3 Vol. 4. Real Function Theory, Differential Equations, Differential Transformations Real Function Theory ( ) Strengthening, or simplifying, the proof of many known results from real analysis

44 Ostrowski p. 21/3 Vol. 4. Real Function Theory, Differential Equations, Differential Transformations Real Function Theory ( ) Strengthening, or simplifying, the proof of many known results from real analysis (1943) Conditions of integrability for partial differential equations

45 Ostrowski p. 21/3 Vol. 4. Real Function Theory, Differential Equations, Differential Transformations Real Function Theory ( ) Strengthening, or simplifying, the proof of many known results from real analysis (1943) Conditions of integrability for partial differential equations (1946) Indefinite integrals of elementary functions (Liouville Theory)

46 Ostrowski p. 21/3 Vol. 4. Real Function Theory, Differential Equations, Differential Transformations Real Function Theory ( ) Strengthening, or simplifying, the proof of many known results from real analysis (1943) Conditions of integrability for partial differential equations (1946) Indefinite integrals of elementary functions (Liouville Theory) (1952) Convex functions in the sense of Schur, with applications to spectral properties of Hermitian matrices

47 Ostrowski p. 21/3 Vol. 4. Real Function Theory, Differential Equations, Differential Transformations Real Function Theory ( ) Strengthening, or simplifying, the proof of many known results from real analysis (1943) Conditions of integrability for partial differential equations (1946) Indefinite integrals of elementary functions (Liouville Theory) (1952) Convex functions in the sense of Schur, with applications to spectral properties of Hermitian matrices (1957) Points of attraction and repulsion for fixed point iteration in Euclidean space

48 Ostrowski p. 22/3 Real Function Theory (continued) (1958) Univalence of nonlinear transformations in Euclidean space

49 Ostrowski p. 22/3 Real Function Theory (continued) (1958) Univalence of nonlinear transformations in Euclidean space (1966) Theory of Fourier transforms

50 Ostrowski p. 22/3 Real Function Theory (continued) (1958) Univalence of nonlinear transformations in Euclidean space (1966) Theory of Fourier transforms ( ) Study of the remainder term in the Euler-Maclaurin formula

51 Ostrowski p. 22/3 Real Function Theory (continued) (1958) Univalence of nonlinear transformations in Euclidean space (1966) Theory of Fourier transforms ( ) Study of the remainder term in the Euler-Maclaurin formula (1970) The (frequently cited) Ostrowski Grüss inequality f(x)g(x)dx f(x)dx g(x)dx osc f max [0,1] [0,1] g 0

52 Ostrowski p. 23/3 Real Function Theory (continued) (1975) Asymptotic expansion of integrals containing a large parameter

53 Ostrowski p. 23/3 Real Function Theory (continued) (1975) Asymptotic expansion of integrals containing a large parameter (1976) Generalized Cauchy-Frullani integral 0 f(at) f(bt) t where 1 M(f) = lim x x dt = [M(f) m(f)] ln a b, a > 0, b > 0 x 1 f(t)dt, m(f) = lim x 0 x 1 x f(t) t 2 dt

54 Ostrowski s 60th birthday Ostrowski p. 24/3

55 Ostrowski p. 25/3 Differential Equations (1919) Göttingen thesis: Dirichlet series and algebraic differential equations

56 Ostrowski p. 25/3 Differential Equations (1919) Göttingen thesis: Dirichlet series and algebraic differential equations (1956) Theory of characteristics for first-order partial differential equations

57 Ostrowski p. 25/3 Differential Equations (1919) Göttingen thesis: Dirichlet series and algebraic differential equations (1956) Theory of characteristics for first-order partial differential equations (1961) A decomposition of an ordinary second-order matrix differential operator

58 Ostrowski p. 25/3 Differential Equations (1919) Göttingen thesis: Dirichlet series and algebraic differential equations (1956) Theory of characteristics for first-order partial differential equations (1961) A decomposition of an ordinary second-order matrix differential operator Differential Transformations ( ) Various classes of contact transformations in the sense of S. Lie

59 Ostrowski p. 25/3 Differential Equations (1919) Göttingen thesis: Dirichlet series and algebraic differential equations (1956) Theory of characteristics for first-order partial differential equations (1961) A decomposition of an ordinary second-order matrix differential operator Differential Transformations ( ) Various classes of contact transformations in the sense of S. Lie (1942) Invertible transformations of line elements

60 Ostrowski p. 26/3 Vol. 5. Complex Function Theory ( ) Gap theorems for power series and related phenomena of overconvergence

61 Ostrowski p. 26/3 Vol. 5. Complex Function Theory ( ) Gap theorems for power series and related phenomena of overconvergence ( ) Investigations related to Picard s theorem

62 Ostrowski p. 26/3 Vol. 5. Complex Function Theory ( ) Gap theorems for power series and related phenomena of overconvergence ( ) Investigations related to Picard s theorem (1929) Quasi-analytic functions, the theory of Carleman

63 Ostrowski p. 26/3 Vol. 5. Complex Function Theory ( ) Gap theorems for power series and related phenomena of overconvergence ( ) Investigations related to Picard s theorem (1929) Quasi-analytic functions, the theory of Carleman (1933, 1955) Analytic continuation of power series and Dirichlet series

64 Ostrowski p. 27/3 Vol. 6. Conformal Mapping, Numerical Analysis, Miscellanea Conformal Mapping (1929) Constructive proof of the Riemann Mapping Theorem

65 Ostrowski p. 27/3 Vol. 6. Conformal Mapping, Numerical Analysis, Miscellanea Conformal Mapping (1929) Constructive proof of the Riemann Mapping Theorem ( ) Boundary behavior of conformal maps

66 Ostrowski p. 27/3 Vol. 6. Conformal Mapping, Numerical Analysis, Miscellanea Conformal Mapping (1929) Constructive proof of the Riemann Mapping Theorem ( ) Boundary behavior of conformal maps (1955) Iterative solution of a nonlinear integral equation for the boundary function of a conformal map, application to the conformal map of an ellipse onto the disk

67 Ostrowski p. 27/3 Vol. 6. Conformal Mapping, Numerical Analysis, Miscellanea Conformal Mapping (1929) Constructive proof of the Riemann Mapping Theorem ( ) Boundary behavior of conformal maps (1955) Iterative solution of a nonlinear integral equation for the boundary function of a conformal map, application to the conformal map of an ellipse onto the disk Numerical Analysis ( ) Newton s method for a single equation and a system of two equations: convergence, error estimates, robustness with respect to rounding

68 The Ostrowskis in their home in Montagnola Ostrowski p. 28/3

69 Ostrowski p. 29/3 Numerical Analysis (continued) (1953) Convergence of relaxation methods for linear n n systems, optimal relaxation parameters for n = 2

70 Ostrowski p. 29/3 Numerical Analysis (continued) (1953) Convergence of relaxation methods for linear n n systems, optimal relaxation parameters for n = 2 (1954) Matrices close to a triangular matrix A = [a ij ], a ij m (i > j), a ij M (i < j), 0 < m < M Theorem All eigenvalues of A are contained in the union of disks i D i, D i = {z C : z a ii δ(m, M)}, where δ(m, M) = Mm 1 n mm 1 n M 1 n m 1 n. The constant δ(m, M) is best possible.

71 Ostrowski p. 30/3 Numerical Analysis (continued) (1956) Absolute convergence of iterative methods for solving linear systems

72 Ostrowski p. 30/3 Numerical Analysis (continued) (1956) Absolute convergence of iterative methods for solving linear systems (1956) Convergence of Steffensen s iteration

73 Ostrowski p. 30/3 Numerical Analysis (continued) (1956) Absolute convergence of iterative methods for solving linear systems (1956) Convergence of Steffensen s iteration (1957) Approximate solution of homogeneous systems of linear equations

74 Ostrowski p. 30/3 Numerical Analysis (continued) (1956) Absolute convergence of iterative methods for solving linear systems (1956) Convergence of Steffensen s iteration (1957) Approximate solution of homogeneous systems of linear equations (1958) A device of Gauss for speeding up iterative methods

75 Ostrowski p. 31/3 Numerical Analysis (continued) (1964) Convergence analysis of Muller s method for solving nonlinear equations

76 Ostrowski p. 31/3 Numerical Analysis (continued) (1964) Convergence analysis of Muller s method for solving nonlinear equations (1967) Convergence of the fixed point iteration in a metric space in the presence of rounding errors

77 Ostrowski p. 31/3 Numerical Analysis (continued) (1964) Convergence analysis of Muller s method for solving nonlinear equations (1967) Convergence of the fixed point iteration in a metric space in the presence of rounding errors (1967) Convergence of the method of steepest descent

78 Ostrowski p. 31/3 Numerical Analysis (continued) (1964) Convergence analysis of Muller s method for solving nonlinear equations (1967) Convergence of the fixed point iteration in a metric space in the presence of rounding errors (1967) Convergence of the method of steepest descent (1969) A descent algorithm for the roots of algebraic equations

79 Ostrowski p. 31/3 Numerical Analysis (continued) (1964) Convergence analysis of Muller s method for solving nonlinear equations (1967) Convergence of the fixed point iteration in a metric space in the presence of rounding errors (1967) Convergence of the method of steepest descent (1969) A descent algorithm for the roots of algebraic equations (1971) Newton s method in Banach spaces

80 Ostrowski p. 31/3 Numerical Analysis (continued) (1964) Convergence analysis of Muller s method for solving nonlinear equations (1967) Convergence of the fixed point iteration in a metric space in the presence of rounding errors (1967) Convergence of the method of steepest descent (1969) A descent algorithm for the roots of algebraic equations (1971) Newton s method in Banach spaces ( ) a posteriori error bounds in iterative processes

81 Ostrowski p. 32/3 Today s Special (1964) A determinant with combinatorial numbers ( x ) ( x ) ( k 0 k 0 x ) 1 k 0 m ( x ) ( x ) ( k 1 k 1 x ) 1 k 1 m ( x ) ) ( k m x ) ( x k m 1 k m m

82 Ostrowski p. 32/3 Today s Special (1964) A determinant with combinatorial numbers ( x ) ( x ) ( k 0 k 0 x ) 1 k 0 m ( x ) ( x ) ( k 1 k 1 x ) 1 k 1 m ( x ) ) ( k m x ) ( x k m 1 k m m = [Γ(x + 1)] m+1 m µ=1 (x + µ)m+1 µ (k 0,..., k m ) m µ=0 [Γ(k µ + 1)Γ(x m k µ )] where (k 0,..., k m ) = λ>µ(k λ k µ )

83 Ostrowski in his 90s Ostrowski p. 33/3

84 Ostrowski p. 34/3 Vol. 6. Miscellaneous Miscellaneous papers on probability distribution functions

85 Ostrowski p. 34/3 Vol. 6. Miscellaneous Miscellaneous papers on probability distribution functions Lectures

86 Ostrowski p. 34/3 Vol. 6. Miscellaneous Miscellaneous papers on probability distribution functions Lectures Book Reviews

87 Ostrowski p. 34/3 Vol. 6. Miscellaneous Miscellaneous papers on probability distribution functions Lectures Book Reviews Obituaries (G. H. Hardy, ; W. Süss, ; Werner Gautschi, )

88 Gentilino Ostrowski p. 35/3

MATH 425-Spring 2010 HOMEWORK ASSIGNMENTS

MATH 425-Spring 2010 HOMEWORK ASSIGNMENTS MATH 425-Spring 2010 HOMEWORK ASSIGNMENTS Instructor: Shmuel Friedland Department of Mathematics, Statistics and Computer Science email: friedlan@uic.edu Last update April 18, 2010 1 HOMEWORK ASSIGNMENT

More information

TEST CODE: PMB SYLLABUS

TEST CODE: PMB SYLLABUS TEST CODE: PMB SYLLABUS Convergence and divergence of sequence and series; Cauchy sequence and completeness; Bolzano-Weierstrass theorem; continuity, uniform continuity, differentiability; directional

More information

MATHEMATICS. Course Syllabus. Section A: Linear Algebra. Subject Code: MA. Course Structure. Ordinary Differential Equations

MATHEMATICS. Course Syllabus. Section A: Linear Algebra. Subject Code: MA. Course Structure. Ordinary Differential Equations MATHEMATICS Subject Code: MA Course Structure Sections/Units Section A Section B Section C Linear Algebra Complex Analysis Real Analysis Topics Section D Section E Section F Section G Section H Section

More information

Introduction to Numerical Analysis

Introduction to Numerical Analysis J. Stoer R. Bulirsch Introduction to Numerical Analysis Second Edition Translated by R. Bartels, W. Gautschi, and C. Witzgall With 35 Illustrations Springer Contents Preface to the Second Edition Preface

More information

E.J. Barbeau. Polynomials. With 36 Illustrations. Springer

E.J. Barbeau. Polynomials. With 36 Illustrations. Springer E.J. Barbeau Polynomials With 36 Illustrations Springer Contents Preface Acknowledgment of Problem Sources vii xiii 1 Fundamentals 1 /l.l The Anatomy of a Polynomial of a Single Variable 1 1.1.5 Multiplication

More information

Contents. 2 Sequences and Series Approximation by Rational Numbers Sequences Basics on Sequences...

Contents. 2 Sequences and Series Approximation by Rational Numbers Sequences Basics on Sequences... Contents 1 Real Numbers: The Basics... 1 1.1 Notation... 1 1.2 Natural Numbers... 4 1.3 Integers... 5 1.4 Fractions and Rational Numbers... 10 1.4.1 Introduction... 10 1.4.2 Powers and Radicals of Rational

More information

University of Houston, Department of Mathematics Numerical Analysis, Fall 2005

University of Houston, Department of Mathematics Numerical Analysis, Fall 2005 3 Numerical Solution of Nonlinear Equations and Systems 3.1 Fixed point iteration Reamrk 3.1 Problem Given a function F : lr n lr n, compute x lr n such that ( ) F(x ) = 0. In this chapter, we consider

More information

Course Description - Master in of Mathematics Comprehensive exam& Thesis Tracks

Course Description - Master in of Mathematics Comprehensive exam& Thesis Tracks Course Description - Master in of Mathematics Comprehensive exam& Thesis Tracks 1309701 Theory of ordinary differential equations Review of ODEs, existence and uniqueness of solutions for ODEs, existence

More information

ENGINEERING MATHEMATICS I. CODE: 10 MAT 11 IA Marks: 25 Hrs/Week: 04 Exam Hrs: 03 PART-A

ENGINEERING MATHEMATICS I. CODE: 10 MAT 11 IA Marks: 25 Hrs/Week: 04 Exam Hrs: 03 PART-A ENGINEERING MATHEMATICS I CODE: 10 MAT 11 IA Marks: 25 Hrs/Week: 04 Exam Hrs: 03 Total Hrs: 52 Exam Marks:100 PART-A Unit-I: DIFFERENTIAL CALCULUS - 1 Determination of n th derivative of standard functions-illustrative

More information

STUDY PLAN MASTER IN (MATHEMATICS) (Thesis Track)

STUDY PLAN MASTER IN (MATHEMATICS) (Thesis Track) STUDY PLAN MASTER IN (MATHEMATICS) (Thesis Track) I. GENERAL RULES AND CONDITIONS: 1- This plan conforms to the regulations of the general frame of the Master programs. 2- Areas of specialty of admission

More information

Review of Power Series

Review of Power Series Review of Power Series MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Introduction In addition to the techniques we have studied so far, we may use power

More information

Fourth Week: Lectures 10-12

Fourth Week: Lectures 10-12 Fourth Week: Lectures 10-12 Lecture 10 The fact that a power series p of positive radius of convergence defines a function inside its disc of convergence via substitution is something that we cannot ignore

More information

Qualifying Exams I, Jan where µ is the Lebesgue measure on [0,1]. In this problems, all functions are assumed to be in L 1 [0,1].

Qualifying Exams I, Jan where µ is the Lebesgue measure on [0,1]. In this problems, all functions are assumed to be in L 1 [0,1]. Qualifying Exams I, Jan. 213 1. (Real Analysis) Suppose f j,j = 1,2,... and f are real functions on [,1]. Define f j f in measure if and only if for any ε > we have lim µ{x [,1] : f j(x) f(x) > ε} = j

More information

Metric Spaces and Topology

Metric Spaces and Topology Chapter 2 Metric Spaces and Topology From an engineering perspective, the most important way to construct a topology on a set is to define the topology in terms of a metric on the set. This approach underlies

More information

1. If 1, ω, ω 2, -----, ω 9 are the 10 th roots of unity, then (1 + ω) (1 + ω 2 ) (1 + ω 9 ) is A) 1 B) 1 C) 10 D) 0

1. If 1, ω, ω 2, -----, ω 9 are the 10 th roots of unity, then (1 + ω) (1 + ω 2 ) (1 + ω 9 ) is A) 1 B) 1 C) 10 D) 0 4 INUTES. If, ω, ω, -----, ω 9 are the th roots of unity, then ( + ω) ( + ω ) ----- ( + ω 9 ) is B) D) 5. i If - i = a + ib, then a =, b = B) a =, b = a =, b = D) a =, b= 3. Find the integral values for

More information

you expect to encounter difficulties when trying to solve A x = b? 4. A composite quadrature rule has error associated with it in the following form

you expect to encounter difficulties when trying to solve A x = b? 4. A composite quadrature rule has error associated with it in the following form Qualifying exam for numerical analysis (Spring 2017) Show your work for full credit. If you are unable to solve some part, attempt the subsequent parts. 1. Consider the following finite difference: f (0)

More information

Chapter 7 Iterative Techniques in Matrix Algebra

Chapter 7 Iterative Techniques in Matrix Algebra Chapter 7 Iterative Techniques in Matrix Algebra Per-Olof Persson persson@berkeley.edu Department of Mathematics University of California, Berkeley Math 128B Numerical Analysis Vector Norms Definition

More information

Problem 1A. Find the volume of the solid given by x 2 + z 2 1, y 2 + z 2 1. (Hint: 1. Solution: The volume is 1. Problem 2A.

Problem 1A. Find the volume of the solid given by x 2 + z 2 1, y 2 + z 2 1. (Hint: 1. Solution: The volume is 1. Problem 2A. Problem 1A Find the volume of the solid given by x 2 + z 2 1, y 2 + z 2 1 (Hint: 1 1 (something)dz) Solution: The volume is 1 1 4xydz where x = y = 1 z 2 This integral has value 16/3 Problem 2A Let f(x)

More information

Numerical Methods in Matrix Computations

Numerical Methods in Matrix Computations Ake Bjorck Numerical Methods in Matrix Computations Springer Contents 1 Direct Methods for Linear Systems 1 1.1 Elements of Matrix Theory 1 1.1.1 Matrix Algebra 2 1.1.2 Vector Spaces 6 1.1.3 Submatrices

More information

1. Foundations of Numerics from Advanced Mathematics. Linear Algebra

1. Foundations of Numerics from Advanced Mathematics. Linear Algebra Foundations of Numerics from Advanced Mathematics Linear Algebra Linear Algebra, October 23, 22 Linear Algebra Mathematical Structures a mathematical structure consists of one or several sets and one or

More information

Mathematics 324 Riemann Zeta Function August 5, 2005

Mathematics 324 Riemann Zeta Function August 5, 2005 Mathematics 324 Riemann Zeta Function August 5, 25 In this note we give an introduction to the Riemann zeta function, which connects the ideas of real analysis with the arithmetic of the integers. Define

More information

Functional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability...

Functional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability... Functional Analysis Franck Sueur 2018-2019 Contents 1 Metric spaces 1 1.1 Definitions........................................ 1 1.2 Completeness...................................... 3 1.3 Compactness......................................

More information

APPENDIX A. Background Mathematics. A.1 Linear Algebra. Vector algebra. Let x denote the n-dimensional column vector with components x 1 x 2.

APPENDIX A. Background Mathematics. A.1 Linear Algebra. Vector algebra. Let x denote the n-dimensional column vector with components x 1 x 2. APPENDIX A Background Mathematics A. Linear Algebra A.. Vector algebra Let x denote the n-dimensional column vector with components 0 x x 2 B C @. A x n Definition 6 (scalar product). The scalar product

More information

Kernel Method: Data Analysis with Positive Definite Kernels

Kernel Method: Data Analysis with Positive Definite Kernels Kernel Method: Data Analysis with Positive Definite Kernels 2. Positive Definite Kernel and Reproducing Kernel Hilbert Space Kenji Fukumizu The Institute of Statistical Mathematics. Graduate University

More information

x x2 2 + x3 3 x4 3. Use the divided-difference method to find a polynomial of least degree that fits the values shown: (b)

x x2 2 + x3 3 x4 3. Use the divided-difference method to find a polynomial of least degree that fits the values shown: (b) Numerical Methods - PROBLEMS. The Taylor series, about the origin, for log( + x) is x x2 2 + x3 3 x4 4 + Find an upper bound on the magnitude of the truncation error on the interval x.5 when log( + x)

More information

MATHEMATICS (MATH) Mathematics (MATH) 1 MATH AP/OTH CREDIT CALCULUS II MATH SINGLE VARIABLE CALCULUS I

MATHEMATICS (MATH) Mathematics (MATH) 1 MATH AP/OTH CREDIT CALCULUS II MATH SINGLE VARIABLE CALCULUS I Mathematics (MATH) 1 MATHEMATICS (MATH) MATH 101 - SINGLE VARIABLE CALCULUS I Short Title: SINGLE VARIABLE CALCULUS I Description: Limits, continuity, differentiation, integration, and the Fundamental

More information

AIMS Exercise Set # 1

AIMS Exercise Set # 1 AIMS Exercise Set #. Determine the form of the single precision floating point arithmetic used in the computers at AIMS. What is the largest number that can be accurately represented? What is the smallest

More information

Final Year M.Sc., Degree Examinations

Final Year M.Sc., Degree Examinations QP CODE 569 Page No Final Year MSc, Degree Examinations September / October 5 (Directorate of Distance Education) MATHEMATICS Paper PM 5: DPB 5: COMPLEX ANALYSIS Time: 3hrs] [Max Marks: 7/8 Instructions

More information

NATIONAL BOARD FOR HIGHER MATHEMATICS. Research Scholarships Screening Test. Saturday, February 2, Time Allowed: Two Hours Maximum Marks: 40

NATIONAL BOARD FOR HIGHER MATHEMATICS. Research Scholarships Screening Test. Saturday, February 2, Time Allowed: Two Hours Maximum Marks: 40 NATIONAL BOARD FOR HIGHER MATHEMATICS Research Scholarships Screening Test Saturday, February 2, 2008 Time Allowed: Two Hours Maximum Marks: 40 Please read, carefully, the instructions on the following

More information

MA257: INTRODUCTION TO NUMBER THEORY LECTURE NOTES

MA257: INTRODUCTION TO NUMBER THEORY LECTURE NOTES MA257: INTRODUCTION TO NUMBER THEORY LECTURE NOTES 2018 57 5. p-adic Numbers 5.1. Motivating examples. We all know that 2 is irrational, so that 2 is not a square in the rational field Q, but that we can

More information

MATHEMATICAL FORMULAS AND INTEGRALS

MATHEMATICAL FORMULAS AND INTEGRALS MATHEMATICAL FORMULAS AND INTEGRALS ALAN JEFFREY Department of Engineering Mathematics University of Newcastle upon Tyne Newcastle upon Tyne United Kingdom Academic Press San Diego New York Boston London

More information

LECTURE NOTES ELEMENTARY NUMERICAL METHODS. Eusebius Doedel

LECTURE NOTES ELEMENTARY NUMERICAL METHODS. Eusebius Doedel LECTURE NOTES on ELEMENTARY NUMERICAL METHODS Eusebius Doedel TABLE OF CONTENTS Vector and Matrix Norms 1 Banach Lemma 20 The Numerical Solution of Linear Systems 25 Gauss Elimination 25 Operation Count

More information

Contents. Preface xi. vii

Contents. Preface xi. vii Preface xi 1. Real Numbers and Monotone Sequences 1 1.1 Introduction; Real numbers 1 1.2 Increasing sequences 3 1.3 Limit of an increasing sequence 4 1.4 Example: the number e 5 1.5 Example: the harmonic

More information

FINITE-DIMENSIONAL LINEAR ALGEBRA

FINITE-DIMENSIONAL LINEAR ALGEBRA DISCRETE MATHEMATICS AND ITS APPLICATIONS Series Editor KENNETH H ROSEN FINITE-DIMENSIONAL LINEAR ALGEBRA Mark S Gockenbach Michigan Technological University Houghton, USA CRC Press Taylor & Francis Croup

More information

Numerical Analysis: Solving Systems of Linear Equations

Numerical Analysis: Solving Systems of Linear Equations Numerical Analysis: Solving Systems of Linear Equations Mirko Navara http://cmpfelkcvutcz/ navara/ Center for Machine Perception, Department of Cybernetics, FEE, CTU Karlovo náměstí, building G, office

More information

OR MSc Maths Revision Course

OR MSc Maths Revision Course OR MSc Maths Revision Course Tom Byrne School of Mathematics University of Edinburgh t.m.byrne@sms.ed.ac.uk 15 September 2017 General Information Today JCMB Lecture Theatre A, 09:30-12:30 Mathematics revision

More information

NATIONAL BOARD FOR HIGHER MATHEMATICS. Research Scholarships Screening Test. Saturday, January 20, Time Allowed: 150 Minutes Maximum Marks: 40

NATIONAL BOARD FOR HIGHER MATHEMATICS. Research Scholarships Screening Test. Saturday, January 20, Time Allowed: 150 Minutes Maximum Marks: 40 NATIONAL BOARD FOR HIGHER MATHEMATICS Research Scholarships Screening Test Saturday, January 2, 218 Time Allowed: 15 Minutes Maximum Marks: 4 Please read, carefully, the instructions that follow. INSTRUCTIONS

More information

Applied Analysis (APPM 5440): Final exam 1:30pm 4:00pm, Dec. 14, Closed books.

Applied Analysis (APPM 5440): Final exam 1:30pm 4:00pm, Dec. 14, Closed books. Applied Analysis APPM 44: Final exam 1:3pm 4:pm, Dec. 14, 29. Closed books. Problem 1: 2p Set I = [, 1]. Prove that there is a continuous function u on I such that 1 ux 1 x sin ut 2 dt = cosx, x I. Define

More information

Numerical Methods - Numerical Linear Algebra

Numerical Methods - Numerical Linear Algebra Numerical Methods - Numerical Linear Algebra Y. K. Goh Universiti Tunku Abdul Rahman 2013 Y. K. Goh (UTAR) Numerical Methods - Numerical Linear Algebra I 2013 1 / 62 Outline 1 Motivation 2 Solving Linear

More information

Real Analysis Problems

Real Analysis Problems Real Analysis Problems Cristian E. Gutiérrez September 14, 29 1 1 CONTINUITY 1 Continuity Problem 1.1 Let r n be the sequence of rational numbers and Prove that f(x) = 1. f is continuous on the irrationals.

More information

CONTENTS. Preface Preliminaries 1

CONTENTS. Preface Preliminaries 1 Preface xi Preliminaries 1 1 TOOLS FOR ANALYSIS 5 1.1 The Completeness Axiom and Some of Its Consequences 5 1.2 The Distribution of the Integers and the Rational Numbers 12 1.3 Inequalities and Identities

More information

Linear Algebra. Min Yan

Linear Algebra. Min Yan Linear Algebra Min Yan January 2, 2018 2 Contents 1 Vector Space 7 1.1 Definition................................. 7 1.1.1 Axioms of Vector Space..................... 7 1.1.2 Consequence of Axiom......................

More information

Nonlinear equations. Norms for R n. Convergence orders for iterative methods

Nonlinear equations. Norms for R n. Convergence orders for iterative methods Nonlinear equations Norms for R n Assume that X is a vector space. A norm is a mapping X R with x such that for all x, y X, α R x = = x = αx = α x x + y x + y We define the following norms on the vector

More information

INDEX. Bolzano-Weierstrass theorem, for sequences, boundary points, bounded functions, 142 bounded sets, 42 43

INDEX. Bolzano-Weierstrass theorem, for sequences, boundary points, bounded functions, 142 bounded sets, 42 43 INDEX Abel s identity, 131 Abel s test, 131 132 Abel s theorem, 463 464 absolute convergence, 113 114 implication of conditional convergence, 114 absolute value, 7 reverse triangle inequality, 9 triangle

More information

MATH3283W LECTURE NOTES: WEEK 6 = 5 13, = 2 5, 1 13

MATH3283W LECTURE NOTES: WEEK 6 = 5 13, = 2 5, 1 13 MATH383W LECTURE NOTES: WEEK 6 //00 Recursive sequences (cont.) Examples: () a =, a n+ = 3 a n. The first few terms are,,, 5 = 5, 3 5 = 5 3, Since 5

More information

MATH 310 Course Objectives

MATH 310 Course Objectives MATH 310 Course Objectives Upon successful completion of MATH 310, the student should be able to: Apply the addition, subtraction, multiplication, and division principles to solve counting problems. Apply

More information

NATIONAL BOARD FOR HIGHER MATHEMATICS. M. A. and M.Sc. Scholarship Test. September 17, Time Allowed: 150 Minutes Maximum Marks: 30

NATIONAL BOARD FOR HIGHER MATHEMATICS. M. A. and M.Sc. Scholarship Test. September 17, Time Allowed: 150 Minutes Maximum Marks: 30 NATIONAL BOARD FOR HIGHER MATHEMATICS M. A. and M.Sc. Scholarship Test September 17, 2016 Time Allowed: 150 Minutes Maximum Marks: 30 Please read, carefully, the instructions that follow INSTRUCTIONS TO

More information

E. F. Beckenbach R. Bellman. Inequalities. Third Printing. '**" '»»..,,. t. Springer-Verlag Berlin Heidelberg New York 1971

E. F. Beckenbach R. Bellman. Inequalities. Third Printing. '** '»»..,,. t. Springer-Verlag Berlin Heidelberg New York 1971 ) E. F. Beckenbach R. Bellman Inequalities Third Printing '**" '»»..,,. t Springer-Verlag Berlin Heidelberg New York 1971 I.! Chapter 1. The Fundamental Inequalities and Related Matters 1 1. Introduction

More information

Advanced Mathematical Methods for Scientists and Engineers I

Advanced Mathematical Methods for Scientists and Engineers I Carl M. Bender Steven A. Orszag Advanced Mathematical Methods for Scientists and Engineers I Asymptotic Methods and Perturbation Theory With 148 Figures Springer CONTENTS! Preface xiii PART I FUNDAMENTALS

More information

LINEAR ALGEBRA BOOT CAMP WEEK 4: THE SPECTRAL THEOREM

LINEAR ALGEBRA BOOT CAMP WEEK 4: THE SPECTRAL THEOREM LINEAR ALGEBRA BOOT CAMP WEEK 4: THE SPECTRAL THEOREM Unless otherwise stated, all vector spaces in this worksheet are finite dimensional and the scalar field F is R or C. Definition 1. A linear operator

More information

INTEGRATION WORKSHOP 2003 COMPLEX ANALYSIS EXERCISES

INTEGRATION WORKSHOP 2003 COMPLEX ANALYSIS EXERCISES INTEGRATION WORKSHOP 23 COMPLEX ANALYSIS EXERCISES DOUGLAS ULMER 1. Meromorphic functions on the Riemann sphere It s often useful to allow functions to take the value. This exercise outlines one way to

More information

Section Taylor and Maclaurin Series

Section Taylor and Maclaurin Series Section.0 Taylor and Maclaurin Series Ruipeng Shen Feb 5 Taylor and Maclaurin Series Main Goal: How to find a power series representation for a smooth function us assume that a smooth function has a power

More information

Courses: Mathematics (MATH)College: Natural Sciences & Mathematics. Any TCCN equivalents are indicated in square brackets [ ].

Courses: Mathematics (MATH)College: Natural Sciences & Mathematics. Any TCCN equivalents are indicated in square brackets [ ]. Courses: Mathematics (MATH)College: Natural Sciences & Mathematics Any TCCN equivalents are indicated in square brackets [ ]. MATH 1300: Fundamentals of Mathematics Cr. 3. (3-0). A survey of precollege

More information

3 (Due ). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure?

3 (Due ). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure? MA 645-4A (Real Analysis), Dr. Chernov Homework assignment 1 (Due ). Show that the open disk x 2 + y 2 < 1 is a countable union of planar elementary sets. Show that the closed disk x 2 + y 2 1 is a countable

More information

The Way of Analysis. Robert S. Strichartz. Jones and Bartlett Publishers. Mathematics Department Cornell University Ithaca, New York

The Way of Analysis. Robert S. Strichartz. Jones and Bartlett Publishers. Mathematics Department Cornell University Ithaca, New York The Way of Analysis Robert S. Strichartz Mathematics Department Cornell University Ithaca, New York Jones and Bartlett Publishers Boston London Contents Preface xiii 1 Preliminaries 1 1.1 The Logic of

More information

SCORE BOOSTER JAMB PREPARATION SERIES II

SCORE BOOSTER JAMB PREPARATION SERIES II BOOST YOUR JAMB SCORE WITH PAST Polynomials QUESTIONS Part II ALGEBRA by H. O. Aliu J. K. Adewole, PhD (Editor) 1) If 9x 2 + 6xy + 4y 2 is a factor of 27x 3 8y 3, find the other factor. (UTME 2014) 3x

More information

NATIONAL BOARD FOR HIGHER MATHEMATICS. Research Awards Screening Test. February 25, Time Allowed: 90 Minutes Maximum Marks: 40

NATIONAL BOARD FOR HIGHER MATHEMATICS. Research Awards Screening Test. February 25, Time Allowed: 90 Minutes Maximum Marks: 40 NATIONAL BOARD FOR HIGHER MATHEMATICS Research Awards Screening Test February 25, 2006 Time Allowed: 90 Minutes Maximum Marks: 40 Please read, carefully, the instructions on the following page before you

More information

Numerical Optimization

Numerical Optimization Numerical Optimization Unit 2: Multivariable optimization problems Che-Rung Lee Scribe: February 28, 2011 (UNIT 2) Numerical Optimization February 28, 2011 1 / 17 Partial derivative of a two variable function

More information

min f(x). (2.1) Objectives consisting of a smooth convex term plus a nonconvex regularization term;

min f(x). (2.1) Objectives consisting of a smooth convex term plus a nonconvex regularization term; Chapter 2 Gradient Methods The gradient method forms the foundation of all of the schemes studied in this book. We will provide several complementary perspectives on this algorithm that highlight the many

More information

Homework and Computer Problems for Math*2130 (W17).

Homework and Computer Problems for Math*2130 (W17). Homework and Computer Problems for Math*2130 (W17). MARCUS R. GARVIE 1 December 21, 2016 1 Department of Mathematics & Statistics, University of Guelph NOTES: These questions are a bare minimum. You should

More information

DEN: Linear algebra numerical view (GEM: Gauss elimination method for reducing a full rank matrix to upper-triangular

DEN: Linear algebra numerical view (GEM: Gauss elimination method for reducing a full rank matrix to upper-triangular form) Given: matrix C = (c i,j ) n,m i,j=1 ODE and num math: Linear algebra (N) [lectures] c phabala 2016 DEN: Linear algebra numerical view (GEM: Gauss elimination method for reducing a full rank matrix

More information

Economics 204 Summer/Fall 2011 Lecture 5 Friday July 29, 2011

Economics 204 Summer/Fall 2011 Lecture 5 Friday July 29, 2011 Economics 204 Summer/Fall 2011 Lecture 5 Friday July 29, 2011 Section 2.6 (cont.) Properties of Real Functions Here we first study properties of functions from R to R, making use of the additional structure

More information

Syllabuses for Honor Courses. Algebra I & II

Syllabuses for Honor Courses. Algebra I & II Syllabuses for Honor Courses Algebra I & II Algebra is a fundamental part of the language of mathematics. Algebraic methods are used in all areas of mathematics. We will fully develop all the key concepts.

More information

Advanced. Engineering Mathematics

Advanced. Engineering Mathematics Advanced Engineering Mathematics A new edition of Further Engineering Mathematics K. A. Stroud Formerly Principal Lecturer Department of Mathematics, Coventry University with additions by Dexter j. Booth

More information

CONSEQUENCES OF POWER SERIES REPRESENTATION

CONSEQUENCES OF POWER SERIES REPRESENTATION CONSEQUENCES OF POWER SERIES REPRESENTATION 1. The Uniqueness Theorem Theorem 1.1 (Uniqueness). Let Ω C be a region, and consider two analytic functions f, g : Ω C. Suppose that S is a subset of Ω that

More information

Introduction to Numerical Analysis

Introduction to Numerical Analysis J. Stoer R. Bulirsch Introduction to Numerical Analysis Translated by R. Bartels, W. Gautschi, and C. Witzgall Springer Science+Business Media, LLC J. Stoer R. Bulirsch Institut fiir Angewandte Mathematik

More information

FIXED POINT ITERATIONS

FIXED POINT ITERATIONS FIXED POINT ITERATIONS MARKUS GRASMAIR 1. Fixed Point Iteration for Non-linear Equations Our goal is the solution of an equation (1) F (x) = 0, where F : R n R n is a continuous vector valued mapping in

More information

MASTERS EXAMINATION IN MATHEMATICS SOLUTIONS

MASTERS EXAMINATION IN MATHEMATICS SOLUTIONS MASTERS EXAMINATION IN MATHEMATICS PURE MATHEMATICS OPTION SPRING 010 SOLUTIONS Algebra A1. Let F be a finite field. Prove that F [x] contains infinitely many prime ideals. Solution: The ring F [x] of

More information

Preliminary/Qualifying Exam in Numerical Analysis (Math 502a) Spring 2012

Preliminary/Qualifying Exam in Numerical Analysis (Math 502a) Spring 2012 Instructions Preliminary/Qualifying Exam in Numerical Analysis (Math 502a) Spring 2012 The exam consists of four problems, each having multiple parts. You should attempt to solve all four problems. 1.

More information

LMI Methods in Optimal and Robust Control

LMI Methods in Optimal and Robust Control LMI Methods in Optimal and Robust Control Matthew M. Peet Arizona State University Lecture 15: Nonlinear Systems and Lyapunov Functions Overview Our next goal is to extend LMI s and optimization to nonlinear

More information

STATE COUNCIL OF EDUCATIONAL RESEARCH AND TRAINING TNCF DRAFT SYLLABUS.

STATE COUNCIL OF EDUCATIONAL RESEARCH AND TRAINING TNCF DRAFT SYLLABUS. STATE COUNCIL OF EDUCATIONAL RESEARCH AND TRAINING TNCF 2017 - DRAFT SYLLABUS Subject :Mathematics Class : XI TOPIC CONTENT Unit 1 : Real Numbers - Revision : Rational, Irrational Numbers, Basic Algebra

More information

5 Compact linear operators

5 Compact linear operators 5 Compact linear operators One of the most important results of Linear Algebra is that for every selfadjoint linear map A on a finite-dimensional space, there exists a basis consisting of eigenvectors.

More information

Given the vectors u, v, w and real numbers α, β, γ. Calculate vector a, which is equal to the linear combination α u + β v + γ w.

Given the vectors u, v, w and real numbers α, β, γ. Calculate vector a, which is equal to the linear combination α u + β v + γ w. Selected problems from the tetbook J. Neustupa, S. Kračmar: Sbírka příkladů z Matematiky I Problems in Mathematics I I. LINEAR ALGEBRA I.. Vectors, vector spaces Given the vectors u, v, w and real numbers

More information

, b = 0. (2) 1 2 The eigenvectors of A corresponding to the eigenvalues λ 1 = 1, λ 2 = 3 are

, b = 0. (2) 1 2 The eigenvectors of A corresponding to the eigenvalues λ 1 = 1, λ 2 = 3 are Quadratic forms We consider the quadratic function f : R 2 R defined by f(x) = 2 xt Ax b T x with x = (x, x 2 ) T, () where A R 2 2 is symmetric and b R 2. We will see that, depending on the eigenvalues

More information

MA3025 Course Prerequisites

MA3025 Course Prerequisites MA3025 Course Prerequisites MA 3025 (4-1) MA3025 (4-1) Logic and Discrete Mathematics: Provides a rigorous foundation in logic and elementary discrete mathematics. Topics from logic include modeling English

More information

Midterm for Introduction to Numerical Analysis I, AMSC/CMSC 466, on 10/29/2015

Midterm for Introduction to Numerical Analysis I, AMSC/CMSC 466, on 10/29/2015 Midterm for Introduction to Numerical Analysis I, AMSC/CMSC 466, on 10/29/2015 The test lasts 1 hour and 15 minutes. No documents are allowed. The use of a calculator, cell phone or other equivalent electronic

More information

Introduction - Motivation. Many phenomena (physical, chemical, biological, etc.) are model by differential equations. f f(x + h) f(x) (x) = lim

Introduction - Motivation. Many phenomena (physical, chemical, biological, etc.) are model by differential equations. f f(x + h) f(x) (x) = lim Introduction - Motivation Many phenomena (physical, chemical, biological, etc.) are model by differential equations. Recall the definition of the derivative of f(x) f f(x + h) f(x) (x) = lim. h 0 h Its

More information

Numerical Methods for Differential Equations Mathematical and Computational Tools

Numerical Methods for Differential Equations Mathematical and Computational Tools Numerical Methods for Differential Equations Mathematical and Computational Tools Gustaf Söderlind Numerical Analysis, Lund University Contents V4.16 Part 1. Vector norms, matrix norms and logarithmic

More information

Hilbert Spaces. Contents

Hilbert Spaces. Contents Hilbert Spaces Contents 1 Introducing Hilbert Spaces 1 1.1 Basic definitions........................... 1 1.2 Results about norms and inner products.............. 3 1.3 Banach and Hilbert spaces......................

More information

Part II. Number Theory. Year

Part II. Number Theory. Year Part II Year 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2017 Paper 3, Section I 1G 70 Explain what is meant by an Euler pseudoprime and a strong pseudoprime. Show that 65 is an Euler

More information

NORTH MAHARASHTRA UNIVERSITY JALGAON.

NORTH MAHARASHTRA UNIVERSITY JALGAON. NORTH MAHARASHTRA UNIVERSITY JALGAON. Syllabus for S.Y.B.Sc. (Mathematics) With effect from June 013. (Semester system). The pattern of examination of theory papers is semester system. Each theory course

More information

Preface. 2 Linear Equations and Eigenvalue Problem 22

Preface. 2 Linear Equations and Eigenvalue Problem 22 Contents Preface xv 1 Errors in Computation 1 1.1 Introduction 1 1.2 Floating Point Representation of Number 1 1.3 Binary Numbers 2 1.3.1 Binary number representation in computer 3 1.4 Significant Digits

More information

BASIC MATRIX ALGEBRA WITH ALGORITHMS AND APPLICATIONS ROBERT A. LIEBLER CHAPMAN & HALL/CRC

BASIC MATRIX ALGEBRA WITH ALGORITHMS AND APPLICATIONS ROBERT A. LIEBLER CHAPMAN & HALL/CRC BASIC MATRIX ALGEBRA WITH ALGORITHMS AND APPLICATIONS ROBERT A. LIEBLER CHAPMAN & HALL/CRC A CRC Press Company Boca Raton London New York Washington, D.C. Contents Preface Examples Major results/proofs

More information

Linear algebra and applications to graphs Part 1

Linear algebra and applications to graphs Part 1 Linear algebra and applications to graphs Part 1 Written up by Mikhail Belkin and Moon Duchin Instructor: Laszlo Babai June 17, 2001 1 Basic Linear Algebra Exercise 1.1 Let V and W be linear subspaces

More information

MATHEMATICAL FORMULAS AND INTEGRALS

MATHEMATICAL FORMULAS AND INTEGRALS HANDBOOK OF MATHEMATICAL FORMULAS AND INTEGRALS Second Edition ALAN JEFFREY Department of Engineering Mathematics University of Newcastle upon Tyne Newcastle upon Tyne United Kingdom ACADEMIC PRESS A Harcourt

More information

TEST CODE: MMA (Objective type) 2015 SYLLABUS

TEST CODE: MMA (Objective type) 2015 SYLLABUS TEST CODE: MMA (Objective type) 2015 SYLLABUS Analytical Reasoning Algebra Arithmetic, geometric and harmonic progression. Continued fractions. Elementary combinatorics: Permutations and combinations,

More information

NUMERICAL MATHEMATICS AND COMPUTING

NUMERICAL MATHEMATICS AND COMPUTING NUMERICAL MATHEMATICS AND COMPUTING Fourth Edition Ward Cheney David Kincaid The University of Texas at Austin 9 Brooks/Cole Publishing Company I(T)P An International Thomson Publishing Company Pacific

More information

Further Mathematics SAMPLE. Marking Scheme

Further Mathematics SAMPLE. Marking Scheme Further Mathematics SAMPLE Marking Scheme This marking scheme has been prepared as a guide only to markers. This is not a set of model answers, or the exclusive answers to the questions, and there will

More information

Hands-on Matrix Algebra Using R

Hands-on Matrix Algebra Using R Preface vii 1. R Preliminaries 1 1.1 Matrix Defined, Deeper Understanding Using Software.. 1 1.2 Introduction, Why R?.................... 2 1.3 Obtaining R.......................... 4 1.4 Reference Manuals

More information

Notation. General. Notation Description See. Sets, Functions, and Spaces. a b & a b The minimum and the maximum of a and b

Notation. General. Notation Description See. Sets, Functions, and Spaces. a b & a b The minimum and the maximum of a and b Notation General Notation Description See a b & a b The minimum and the maximum of a and b a + & a f S u The non-negative part, a 0, and non-positive part, (a 0) of a R The restriction of the function

More information

MATHEMATICS (MATH) Mathematics (MATH) 1

MATHEMATICS (MATH) Mathematics (MATH) 1 Mathematics (MATH) 1 MATHEMATICS (MATH) MATH 1010 Applied Business Mathematics Mathematics used in solving business problems related to simple and compound interest, annuities, payroll, taxes, promissory

More information

INFINITE SEQUENCES AND SERIES

INFINITE SEQUENCES AND SERIES 11 INFINITE SEQUENCES AND SERIES INFINITE SEQUENCES AND SERIES In section 11.9, we were able to find power series representations for a certain restricted class of functions. INFINITE SEQUENCES AND SERIES

More information

MATHEMATICS (MATH) Mathematics (MATH) 1

MATHEMATICS (MATH) Mathematics (MATH) 1 Mathematics (MATH) 1 MATHEMATICS (MATH) MATH F113X Numbers and Society (m) Numbers and data help us understand our society. In this course, we develop mathematical concepts and tools to understand what

More information

1 Math 241A-B Homework Problem List for F2015 and W2016

1 Math 241A-B Homework Problem List for F2015 and W2016 1 Math 241A-B Homework Problem List for F2015 W2016 1.1 Homework 1. Due Wednesday, October 7, 2015 Notation 1.1 Let U be any set, g be a positive function on U, Y be a normed space. For any f : U Y let

More information

Cambridge University Press The Mathematics of Signal Processing Steven B. Damelin and Willard Miller Excerpt More information

Cambridge University Press The Mathematics of Signal Processing Steven B. Damelin and Willard Miller Excerpt More information Introduction Consider a linear system y = Φx where Φ can be taken as an m n matrix acting on Euclidean space or more generally, a linear operator on a Hilbert space. We call the vector x a signal or input,

More information

Jim Lambers MAT 610 Summer Session Lecture 2 Notes

Jim Lambers MAT 610 Summer Session Lecture 2 Notes Jim Lambers MAT 610 Summer Session 2009-10 Lecture 2 Notes These notes correspond to Sections 2.2-2.4 in the text. Vector Norms Given vectors x and y of length one, which are simply scalars x and y, the

More information

Lecture 5. Ch. 5, Norms for vectors and matrices. Norms for vectors and matrices Why?

Lecture 5. Ch. 5, Norms for vectors and matrices. Norms for vectors and matrices Why? KTH ROYAL INSTITUTE OF TECHNOLOGY Norms for vectors and matrices Why? Lecture 5 Ch. 5, Norms for vectors and matrices Emil Björnson/Magnus Jansson/Mats Bengtsson April 27, 2016 Problem: Measure size of

More information

The Hardy-Littlewood Function

The Hardy-Littlewood Function Hardy-Littlewood p. 1/2 The Hardy-Littlewood Function An Exercise in Slowly Convergent Series Walter Gautschi wxg@cs.purdue.edu Purdue University Hardy-Littlewood p. 2/2 OUTLINE The Hardy-Littlewood (HL)

More information

Linear Algebra: Matrix Eigenvalue Problems

Linear Algebra: Matrix Eigenvalue Problems CHAPTER8 Linear Algebra: Matrix Eigenvalue Problems Chapter 8 p1 A matrix eigenvalue problem considers the vector equation (1) Ax = λx. 8.0 Linear Algebra: Matrix Eigenvalue Problems Here A is a given

More information

From Wikipedia, the free encyclopedia

From Wikipedia, the free encyclopedia 1 of 8 27/03/2013 12:41 Quadratic form From Wikipedia, the free encyclopedia In mathematics, a quadratic form is a homogeneous polynomial of degree two in a number of variables. For example, is a quadratic

More information