- Chapter 1: WHERE PDEs COME FROM
- Chapter 10: BOUNDARIES IN THE PLANE AND IN SPACE
- Chapter 11: GENERAL EIGENVALUE PROBLEMS
- Chapter 12: DISTRIBUTIONS AND TRANSFORMS
- Chapter 13: PDE PROBLEMS FROM PHYSICS
- Chapter 14: NONLINEAR PDES
- Chapter 2: WAVES AND DIFFUSIONS
- Chapter 3: REFLECTIONS AND SOURCES
- Chapter 4: BOUNDARY PROBLEMS
- Chapter 5: FOURIER SERIES
- Chapter 6: HARMONIC FUNCTIONS
- Chapter 7: GREENS IDENTITIES AND GREENS FUNCTIONS
- Chapter 8: COMPUTATION OF SOLUTIONS
- Chapter 9: WAVES IN SPACE
Partial Differential Equations: An Introduction 2nd Edition - Solutions by Chapter
Full solutions for Partial Differential Equations: An Introduction | 2nd Edition
ISBN: 9780470054567
Partial Differential Equations: An Introduction | 2nd Edition - Solutions by Chapter
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Key Math Terms and definitions covered in this textbook
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Complete solution x = x p + Xn to Ax = b.
(Particular x p) + (x n in nullspace).
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Factorization
A = L U. If elimination takes A to U without row exchanges, then the lower triangular L with multipliers eij (and eii = 1) brings U back to A.
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Free columns of A.
Columns without pivots; these are combinations of earlier columns.
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Full row rank r = m.
Independent rows, at least one solution to Ax = b, column space is all of Rm. Full rank means full column rank or full row rank.
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Hankel matrix H.
Constant along each antidiagonal; hij depends on i + j.
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Hilbert matrix hilb(n).
Entries HU = 1/(i + j -1) = Jd X i- 1 xj-1dx. Positive definite but extremely small Amin and large condition number: H is ill-conditioned.
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Identity matrix I (or In).
Diagonal entries = 1, off-diagonal entries = 0.
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Incidence matrix of a directed graph.
The m by n edge-node incidence matrix has a row for each edge (node i to node j), with entries -1 and 1 in columns i and j .
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Length II x II.
Square root of x T x (Pythagoras in n dimensions).
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Linear transformation T.
Each vector V in the input space transforms to T (v) in the output space, and linearity requires T(cv + dw) = c T(v) + d T(w). Examples: Matrix multiplication A v, differentiation and integration in function space.
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Multiplication Ax
= Xl (column 1) + ... + xn(column n) = combination of columns.
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Norm
IIA II. The ".e 2 norm" of A is the maximum ratio II Ax II/l1x II = O"max· Then II Ax II < IIAllllxll and IIABII < IIAIIIIBII and IIA + BII < IIAII + IIBII. Frobenius norm IIAII} = L La~. The.e 1 and.e oo norms are largest column and row sums of laij I.
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Outer product uv T
= column times row = rank one matrix.
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Positive definite matrix A.
Symmetric matrix with positive eigenvalues and positive pivots. Definition: x T Ax > 0 unless x = O. Then A = LDLT with diag(D» O.
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Rank one matrix A = uvT f=. O.
Column and row spaces = lines cu and cv.
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Rotation matrix
R = [~ CS ] rotates the plane by () and R- 1 = RT rotates back by -(). Eigenvalues are eiO and e-iO , eigenvectors are (1, ±i). c, s = cos (), sin ().
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Row space C (AT) = all combinations of rows of A.
Column vectors by convention.
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Schwarz inequality
Iv·wl < IIvll IIwll.Then IvTAwl2 < (vT Av)(wT Aw) for pos def A.
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Similar matrices A and B.
Every B = M-I AM has the same eigenvalues as A.
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Volume of box.
The rows (or the columns) of A generate a box with volume I det(A) I.