MATH 54 FINAL EXAM STUDY GUIDE

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MATH 54 FINAL EXAM STUDY GUIDE PEYAM RYAN TABRIZIAN This is the study guide for the final exam! It says what it does: to guide you with your studying for the exam! The terms in boldface are more important than others, so make sure to study them in detail! Note: Remember that the final exam is cumulative. Suggestion: Start with the differential equations-part, since it s fresh in your mind. Once you re done with that, turn your attention to the linear algebra-part. DIFFERENTIAL EQUATIONS Chapter 4: Linear Second-order equations Find the general solution to a second-order differential equation, possibly including complex roots, repeated roots, or initial conditions (4.2.1, 4.2.5, 4.2.15, 4.3.5, 4.3.11, 4.3.23) Determine if two functions are linearly independent or linearly dependent (4.2.27, 4.2.30) Solve equations using undetermined coefficients (4.4.14, 4.4.27, 4.4.31, 4.5.27, 4.5.35) Solve equations using variation of parameters (4.6.3, 4.6.11) Chapter 6: Theory of higher-order linear differential equations Find the largest interval on which a differential equation has a unique solution (6.1.3, 6.1.5) Determine if a set of functions is linearly independent or linearly dependent (6.1.9, 6.1.14, 6.1.13, 6.2.25) Show that given functions form a fundamental solution set for a differential equation (6.1.15, 6.1.17, 6.1.19) Date: Tuesday, May 12, 2015. 1

2 PEYAM RYAN TABRIZIAN Find the general solution of a higher-order differential equation, possibly including initial conditions (6.2.7, 6.2.11, 6.2.15, 6.2.17, 6.2.19, 6.2.20); know the technique using the rational roots theorem and long-division. Chapter 9: Matrix methods for linear systems Convert a higher-order equation into a system of differential equations (9.1.13) Determine if a set of vector functions is linearly independent or linearly dependent, using the Wronskian (9.4.16, 9.4.17) Determine if vector functions form a fundamental solution set for x = Ax Find the general solution to x = Ax, possibly including complex eigenvalues (9.5.13, 9.5.15, 9.5.21, 9.5.31, 9.5.33, 9.6.1, 9.6.9, 9.6.13) Solve x = Ax, where A is not diagonalizable (9.5.35, 9.5.36) Solve x = Ax + f using undetermined coefficients. (9.7.3, 9.7.9, 9.7.10) Note: Remember that variation of parameters for systems will not be on the exam Find e At : - By diagonalizing A (9.8.9) - By using the definition and the fact that (A λi) k = 0 for some k (this only works when A has only one eigenvalue and one eigenvector) (9.8.5) - By using generalized eigenvectors (9.8.11) Use e At to solve x = Ax (9.8.21) Chapter 10: Partial differential equations Calculate the Fourier series of a function f on a given interval, and determine to which function that Fourier series converges (10.3.9, 10.3.11, 10.3.15, 10.3.17, 10.3.19, 10.3.23) Calculate the Fourier cosine/sine series for a function f, and determine to which function that Fourier series converges to (10.4.5, 10.4.7, 10.4.13). Using separation of variables, solve the heat/wave/laplace s equation, subject to various boundary/initial conditions (10.2.15, 10.2.21,

MATH 54 FINAL EXAM STUDY GUIDE 3 10.5.1, 10.5.3, 10.5.5, 10.5.7, 10.6.1, 10.6.3, 10.7.1, 10.7.5). You ARE responsible for heat/wave/laplace s equations with inhomogeneous boundary conditions (see 10.5.7) and inhomogeneous heat/wave equations (see 10.5.9 and the example Prof. Vojta did on page 4 of his May 1-notes), but first focus on solving the problems above, as they are more important. Note: Remember that the following Chapter 10 topics will NOT be on the final exam: - Heat equation in higher dimensions (Example 4 in 10.5) - Traveling waves/d Alembert s formula (pages 617-619 in 10.6) - Laplace s equation on a disk (for section 10.7, you re only responsible for Example 1) LINEAR ALGEBRA Suggestion: Ignore chapters 1, 2, 3, because you basically already know how to do them! Instead, focus on chapters 4, 5, 6, 7 Chapter 4: Vector Spaces Determine if a set is a vector space or not (4.1.3, 4.1.9, 4.2.7, 4.2.9) Determine whether a set is linear independent or dependent (4.3.3, 4.4.27) Find a basis and state the dimension of a vector space (4.5.7, 4.5.11) Given a matrix A, find a basis for Nul(A), Col(A), Row(A), and also find Rank(A) (4.5.15, 4.6.1, 4.6.3) Use the rank-nullity theorem to find Rank(A) etc. (4.6.5, 4.6.9, 4.6.11, 4.6.15, 4.6.22) Find the change-of-coordinates matrix from B to C (4.4.1, 4.4.3, 4.4.5, 4.4.7, 4.4.11, 4.7.5, 4.7.7, 4.7.9) Use the change-of-coordinates matrix to find [x] C [x] B (4.7.1, 4.7.3); also know how to do this for polynomials (4.7.13)

4 PEYAM RYAN TABRIZIAN Chapter 5: Diagonalization Don t focus too much on this chapter, because it s almost the same as Chapter 9. Find a diagonal matrix D and a matrix P such that A = P DP 1, or say A is not diagonalizable (5.2.9, 5.2.11, 5.3.9, 5.3.11, 5.3.17) Show that a given matrix is not diagonalizable (5.3.8, 5.3.11) Find the matrix of a linear transformation (5.4.1, 5.4.3, 5.4.9, 5.4.11, 5.4.17(b)); also know how to do this for more abstract examples, like matrices or polynomials (see for example Peyam s midterm 2) Note: We will not ask about complex eigenvalues, except maybe in the form of a Chapter 9 - question! Chapter 6: Inner Products and Norms Find a basis for W (all you do is find a basis for W, and find all vectors which are perpendicular to the vectors in the basis, just like the question above) Find the orthogonal projection of x on a subspace W. Use this to write x as a sum of two orthogonal vectors, and to find the smallest distance between x and W (6.2.11, 6.3.3, 6.3.5, 6.3.1, 6.3.7, 6.2.15, 6.3.11) Use the Gram-Schmidt process to produce an orthonormal basis of a subspace W spanned by some vectors (6.4.9, 6.4.11) Find the QR-factorization of a matrix (6.5.13, 6.5.15). Find the least-squares solution (and least-squares error) of an inconsistent system of equations (6.5.1, 6.5.3, 6.5.7, 6.5.9, 6.5.11) Find inner products, lengths, and orthogonal projections of functions f and g using fancier inner products f, g (6.7.3, 6.7.5, 6.7.7, 6.7.9, 6.7.11, 6.7.21, 6.7.23) Use the Gram-Schmidt process to find an orthonormal basis of functions (6.7.25, 6.7.26) Remember the Cauchy-Schwarz inequality (6.7.19, 6.7.20) Chapter 7: Symmetric matrices and quadratic forms Given a symmetric matrix A, find an diagonal matrix D and an orthogonal matrix P such that A = P DP T (7.1.13, 7.1.15, 7.1.17)

MATH 54 FINAL EXAM STUDY GUIDE 5 CONCEPTS Understand the following concepts: - Pivots (1.2, 1.5) - Span (1.3, 1.4) - Linear independence (1.7) - One-to-one and onto (1.9) - Invertible matrices (2.2) - Know all the implications of the Invertible Matrix Theorem (2.3, including page 144) - Subspace, Basis (2.6) - Nul(A), Col(A), The Rank Theorem (2.6, 4.6) - Vector space, Subspace (4.1) - Basis, Dimension (4.3, 4.5) - Coordinates of x with respect to B (4.4) - Basis, Dimension (4.5) - Change of coordinates matrix (4.7) - Eigenvalues, Eigenvectors, Characteristic polynomial (5.1-5.3) - A is similar to B (5.2) - Diagonalizable, Diagonalization Theorem (Theorem 5 in section 5.3) - Matrix of a Linear transformation (5.4) - Inner products, Norms, Orthogonal vectors, Orthogonal Matrix (6.1) - W (6.1) - (Row(A)) = Nul(A), (Col(A)) = Nul(A T ) (Theorem 3 in 6.1) - Orthogonal projection (6.2, 6.3) - Least-squares solution (6.4) - Inner product, inner product space (6.7) - Cauchy-Schwarz and Triangle Inequality (6.7) - Orthogonally diagonalizable (7.1) - Existence and Uniqueness Theorem for differential equations (6.1) - Linear independence of functions/vector functions and Wronskian/fundamental matrix (4.2, 6.1, 9.4) - Fundamental solution set (6.1, 9.4) - Exponential of a matrix (9.8) - Separation of variables (10.2) - Fourier series, Fourier cosine/sine series (10.3, 10.4) - Pointwise convergence of Fourier series (10.3) - Orthogonal expansions (10.3) - Maximum principle (10.5), Conservation of Energy (10.6)