 Chapter 1: Speaking Mathematically
 Chapter 10: Graphs and Trees
 Chapter 2: THE LOGIC OF COMPOUND STATEMENTS
 Chapter 3: The Logic of Quantied Statements
 Chapter 4: Elementary Number Theory and Methods of Proof
 Chapter 5: Sequences, Mathematical Induction, and Recursion
 Chapter 6: Set Theory
 Chapter 7: Functions
 Chapter 8: Relations
 Chapter 9: Counting and Probability
Discrete Mathematics: Introduction to Mathematical Reasoning 1st Edition  Solutions by Chapter
Full solutions for Discrete Mathematics: Introduction to Mathematical Reasoning  1st Edition
ISBN: 9780495826170
Discrete Mathematics: Introduction to Mathematical Reasoning  1st Edition  Solutions by Chapter
Get Full SolutionsSince problems from 10 chapters in Discrete Mathematics: Introduction to Mathematical Reasoning have been answered, more than 15132 students have viewed full stepbystep answer. Discrete Mathematics: Introduction to Mathematical Reasoning was written by and is associated to the ISBN: 9780495826170. This textbook survival guide was created for the textbook: Discrete Mathematics: Introduction to Mathematical Reasoning, edition: 1. The full stepbystep solution to problem in Discrete Mathematics: Introduction to Mathematical Reasoning were answered by , our top Math solution expert on 01/04/18, 08:37PM. This expansive textbook survival guide covers the following chapters: 10.

Associative Law (AB)C = A(BC).
Parentheses can be removed to leave ABC.

Block matrix.
A matrix can be partitioned into matrix blocks, by cuts between rows and/or between columns. Block multiplication ofAB is allowed if the block shapes permit.

Cholesky factorization
A = CTC = (L.J]))(L.J]))T for positive definite A.

Echelon matrix U.
The first nonzero entry (the pivot) in each row comes in a later column than the pivot in the previous row. All zero rows come last.

Eigenvalue A and eigenvector x.
Ax = AX with x#O so det(A  AI) = o.

Four Fundamental Subspaces C (A), N (A), C (AT), N (AT).
Use AT for complex A.

Graph G.
Set of n nodes connected pairwise by m edges. A complete graph has all n(n  1)/2 edges between nodes. A tree has only n  1 edges and no closed loops.

Hilbert matrix hilb(n).
Entries HU = 1/(i + j 1) = Jd X i 1 xj1dx. Positive definite but extremely small Amin and large condition number: H is illconditioned.

Krylov subspace Kj(A, b).
The subspace spanned by b, Ab, ... , AjIb. Numerical methods approximate A I b by x j with residual b  Ax j in this subspace. A good basis for K j requires only multiplication by A at each step.

Outer product uv T
= column times row = rank one matrix.

Pascal matrix
Ps = pascal(n) = the symmetric matrix with binomial entries (i1~;2). Ps = PL Pu all contain Pascal's triangle with det = 1 (see Pascal in the index).

Pivot.
The diagonal entry (first nonzero) at the time when a row is used in elimination.

Polar decomposition A = Q H.
Orthogonal Q times positive (semi)definite H.

Rank one matrix A = uvT f=. O.
Column and row spaces = lines cu and cv.

Rayleigh quotient q (x) = X T Ax I x T x for symmetric A: Amin < q (x) < Amax.
Those extremes are reached at the eigenvectors x for Amin(A) and Amax(A).

Reduced row echelon form R = rref(A).
Pivots = 1; zeros above and below pivots; the r nonzero rows of R give a basis for the row space of A.

Row picture of Ax = b.
Each equation gives a plane in Rn; the planes intersect at x.

Skewsymmetric matrix K.
The transpose is K, since Kij = Kji. Eigenvalues are pure imaginary, eigenvectors are orthogonal, eKt is an orthogonal matrix.

Spanning set.
Combinations of VI, ... ,Vm fill the space. The columns of A span C (A)!

Spectral Theorem A = QAQT.
Real symmetric A has real A'S and orthonormal q's.